Nigel Gilbert

Professor Nigel Gilbert


Professor of Sociology
CBE PhD ScD FREng FAcSS FRSA

Biography

Research

Research interests

Research projects

Supervision

Postgraduate research supervision

My publications

Highlights

Researching Social Life, fourth edition, 2016, edited by Nigel Gilbert and Paul Stoneman, Sage Publications.

 

Simulation for the Social Scientist, second edition 2005, Nigel Gilbert and Klaus G. Troitzsch, Open University Press (also available in Japanese, Russian and Spanish).

Understanding Social Statistics, 2000, Jane Fielding and Nigel Gilbert, Sage Publications.

Opening Pandora's Box, available online (2003), Cambridge University Press, 1984.

Publications

Gilbert GN (1986) Computer help with welfare benefits, Computer Bulletin 1 (3) pp. 2-4
Schiller F, Skeldon A, Balke T, Grant M, Penn AS, Basson L, Jensen P, Gilbert N, Kalkan OD, Woodward A (2014) Defining Relevance and Finding Rules: An Agent-Based Model of Biomass Use in the Humber Area, ADVANCES IN SOCIAL SIMULATION 229 pp. 373-384 SPRINGER-VERLAG BERLIN
DAWSON P, BUCKLAND S, GILBERT N (1990) EXPERT SYSTEMS AND THE PUBLIC PROVISION OF WELFARE BENEFIT ADVICE, POLICY AND POLITICS 18 (1) pp. 43-54 SCH ADV URBAN STUDIES
Gilbert GN, Heath C (1985) Social action and artificial intelligence, Gower
Dale A, Gilbert GN, Arber S (1985) Integrating women into class theory, Sociology 19 pp. 384-409
Gilbert GN, Pyka A, Ahrweiler P (2009) Agent-based modelling of innovation networks: the fairytale of
spillover,
In: Pyka A, Scharnhorst A (eds.), Innovation networks: new approaches in modelling and analyzing 5 pp. 101-126 Springer Verlag
Gilbert GN (1978) Measuring the growth of science - A review of indicators of scientific growth, Scientometrics: an international journal for all quantitative aspects of the science of science, communication in science and science policy 1 (1) pp. 9-34
A number of indicators of the growth of science are critically reviewed to asses their strengths and weaknesses. The focus is on the problems involved in measuring two aspects of scientific growth, growth in manpower and growth in knowledge. It is shown that the design of better indicators depends on careful consideration of the theoretical framework within which the indicators are intended to be used. Recent advances in the sociology of science suggest ways in which the validity of existing indicators may be assessed and improved.
Luff P, Frohlich D, Gilbert GN (1990) Computers and conversation, Academic Press
In the past few years a branch of sociology, conversation analysis, has begun to have a significant impact on the design of human*b1computer interaction (HCI). The investigation of human*b1human dialogue has emerged as a fruitful foundation for interactive system design.****This book includes eleven original chapters by leading researchers who are applying conversation analysis to HCI. The fundamentals of conversation analysis are outlined, a number of systems are described, and a critical view of their value for HCI is offered.****Computers and Conversation will be of interest to all concerned with HCI issues--from the advanced student to the professional computer scientist involved in the design and specification of interactive systems.
Gilbert N (2008) Researching social life, In: Researching social life Abstract Sage Publications Ltd
The Third Edition of Nigel Gilbert's hugely successful Researching Social Life covers the whole range of methods from quantitative to qualitative in a down-to-earth and unthreatening manner.

Gilbert's text offers the best coverage of the full scope of research methods of any of the leading textbooks in the field, making this an essential text for any student starting a research methods course or doing a research project.

This thoroughly revised text is driven by the expertise of a writing team comprised of internationally-renowned experts in the field.

New to the Third Edition are chapters on:

- Searching and Reviewing the Literature

- Refining the Question

- Grounded Theory and Inductive Research

- Mixed Methods

- Participatory Action Research

- Virtual Methods

- Narrative Analysis

A number of useful features, such as worked examples, case studies, discussion questions, project ideas and checklists are included throughout the book to help those new to research to engage with the material.

Researching Social Life follows the 'life cycle' of a typical research project, from initial conception through to eventual publication. Its breadth and depth of coverage make this an indispensable must-have textbook for students on social research methods courses in any discipline.

Gilbert, Stoneman (2015) Researching Social Life: 4th Edition, SAGE
Burrows R, Gilbert GN, Pollert A (1991) Fordism and flexibility: divisions and change, Macmillan
Gilbert N (2007) Who wants to know?, Engineer 293 (7721)
Some of the issues related with the specification, design, and implementation of innovative information technology (IT) systems are raised by a report prepared by the Royal Academy of Engineering. These factors enable to access records of various organizations and services, including medical records and provide better security against theft, violence and privacy. These factors also enable designing travel and shopping services, with better security without revealing the identity of the people involved in these services. People can sign up for a loyalty card without registering their personal details, enabling them to decide about information, which is related to them. The report also suggests that the government needs to be prepared for events of leakage of personal information or privacy of customers when such systems fail.
Gilbert N, Ahrweiler P, Pyka A (2007) Learning in innovation networks: Some simulation experiments, PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 378 (1) pp. 100-109 ELSEVIER SCIENCE BV
Arber S, Gilbert G (1989) Transitions in caring: Gender, Life Course and the care of the Elderly, In: Bytheway W (eds.), Becoming and being old pp. 72-93 Sage
Gilbert GN (1987) Cognitive and social models of the user, In: Bullinger HJ, B.Schakel (eds.), Human-Computer Interaction - Interact ?87 pp. 165-172 North-Holland
Gilbert Nigel, Anzola D, Johnson P, Elsenbroich C, Balke T, Dilaver Kalkan O (2015) Self-organizing dynamical systems, In: International Encyclopedia of the Social & Behavioral Sciences 21 pp. 529-534 Elsevier
The concept of self-organization in social science is reviewed. In the first two sections, some basic features of self-organizing dynamical systems in general science are presented and the origin of the concept is reconstructed, paying special attention to social science accounts of self-organization. Then, theoretical and methodological considerations regarding the current application of the concept and prospective challenges are examined.
Hare M, Gilbert N, Medugno D, Asakawa T, Heeb J, Pahl-Wostl C (2001) The development of an internet forum for long-term participatory group learning about problems and solutions to sustainable urban water supply management, In: Hilty LM, Gilgen PW (eds.), Sustainability in the Information society pp. 743-750 Metropolis
Hassan S, Antunes L, Gilbert N (2010) Going back home - Social simulation and artificial intelligence, Computational and Mathematical Organization Theory pp. 1-4
Ahrweiler P, Gilbert N, Pyka A (2006) Institutions matter but... Organisational alignment in knowledge-based industries, Science, Technology and Innovation Studies 1 (2) pp. 39-58
Gilbert GN, Arber S, Dale A (1982) The Crosslinker: a computer program for the analysis of hierarchical data sets using non-hierarchical analysis packages, SSRC Data Archive Bulletin (22) pp. 7-10
Schuster S, Gilbert N (2004) Simulating Online Business Models, In: Coleho H, Espinasse B, Seidel M (eds.), 5th Workshop on Agent-Based Simulation pp. 55-61 Society for Modeling and Simulation International
Gilbert N (1998) Simulation: an introduction to the idea, In: Ahrweiler P, Gilbert N (eds.), Computer simulations in science and technology studies pp. 1-14 Springer
Gilbert N, Ahrweiler P, Pyka A (2001) Understanding innovation networks through simulation, CD-ROM Delft Technical university
Mulkay MJ, Gilbert GN, Woolgar S (1975) Problem areas and research networks in science, Sociology 9 pp. 187-204
Hassan S, Antunes L, Gilbert N (2010) Going back home Social simulation and artificial intelligence, COMPUTATIONAL AND MATHEMATICAL ORGANIZATION THEORY 16 (4) pp. 325-328 SPRINGER
Kolkman D, Campo P, Balke-Visser T, Gilbert GN (2016) How to build models for government: criteria driving model acceptance in policymaking, Policy Sciences 49 (4) pp. 489-504 Springer
Models are used to inform policymaking and underpin large amounts of government expenditure. Several authors have observed a discrepancy between the actual and potential use of models in government. While there have been several studies investigating model acceptance in government, it remains unclear under what conditions models are accepted. In this paper, we address the question ??What criteria affect model acceptance in policymaking???, the answer to which will contribute to the wider understanding of model use in government. We employ a thematic coding approach to identify the acceptance criteria for the eight models in our sample. Subsequently, we compare our findings with existing literature and use qualitative comparative analysis to explore what configurations of the criteria are observed in instances of model acceptance. We conclude that model acceptance is affected by a combination of the model?s characteristics, the supporting infrastructure and organizational factors.
Abdou M, Gilbert GN (2009) Modelling the emergence and dynamics of social and workplace segregation, Mind and Society 8 (2) pp. 173-191
The relationship between social segregation and workplace segregation has been traditionally studied as a one-way causal relationship mediated by referral hiring. In this paper we introduce an alternative framework which describes the dynamic relationships between social segregation, workplace segregation, individuals? homophily levels, and referral hiring. An agent-based simulation model was developed based on this framework. The model describes the process of continuous change in composition of workplaces and social networks of agents, and how this process affects levels of workplace segregation and the segregation of social networks of the agents (people). It is concluded that: (1) social segregation and workplace segregation may co-evolve even when hiring of workers occurs mainly through formal channels and the population is initially integrated (2) majority groups tend to be more homophilous than minority groups, and (3) referral hiring may be beneficial for minority groups when the population is highly segregated.
Gilbert GN, Arber S, Dale A (1983) Access to social science data in schools, Computers and Education 7 pp. 135-139
Sichman JS, Conte R, Gilbert N (1998) Multi-agent systems and agent-based simulation, Springer
Gilbert N, Ahrweiler P (2009) The Epistemologies of Social Simulation Research, EPISTEMOLOGICAL ASPECTS OF COMPUTER SIMULATION IN THE SOCIAL SCIENCES 5466 pp. 12-28 SPRINGER-VERLAG BERLIN
Gill AJ, Xenitidou M, Gilbert N (2011) Understanding quality in science: A proposal and exploration, Proceedings - 2010 4th IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshop, SASOW 2010 pp. 116-121
Gilbert N (2004) Open problems in using agent-based models in industrial and labor dynamics, Advances in complex systems 7 (2) pp. 285-288
Hamill L, Gilbert N (2010) Simulating large social networks in agent-based models: A social circle model, Emergence: Complexity and Organization 12 (4) pp. 78-94
Gilbert GN (1987) Question and answer types, In: Moralee S (eds.), Research and development in expert systems IV pp. 162-172 Cambridge University Press
Gilbert GN (1984) Statistical Packages on microcomputers, ESRC Data Archive Bulletin (27) pp. 51-52
GILBERT GN (1986) OCCUPATIONAL CLASSES AND INTER-CLASS MOBILITY, BRITISH JOURNAL OF SOCIOLOGY 37 (3) pp. 370-391 ROUTLEDGE
Gilbert N (2007) Agent-based models, Sage Publications Inc.
Lorincz A, Gilbert GN, Goolsby R (2007) Social network analysis: Measuring tools, structures and dynamics, Physica a-Statistical Mechanics and Its Applications 378 (1) pp. XI-XIII
Anzola D, Barbrook-Johnson P, Salgado M, Gilbert Nigel (2017) Sociology and Non-Equilibrium Social Science, In: Johnson J, Nowak A, Ormerod P, Rosewell B, Zhang Y-C (eds.), Non-Equilibrium Social Science and Policy: Introduction and Essays on New and Changing Paradigms in Socio-Economic Thinking (4) 4 pp. 59-69 Springer International Publishing
Abstract This chapter addresses the relationship between sociology and Non- Equilibrium Social Science (NESS). Sociology is a multiparadigmatic discipline with significant disagreement regarding its goals and status as a scientific discipline. Different theories and methods coexist temporally and geographically. However, it has always aimed at identifying the main factors that explain the temporal stability of norms, institutions and individuals? practices; and the dynamics of institutional change and the conflicts brought about by power relations, economic and cultural inequality and class struggle. Sociologists considered equilibrium could not sufficiently explain the constitutive, maintaining and dissolving dynamics of society as a whole. As a move from the formal apparatus for the study of equilibrium, NESS does not imply a major shift from traditional sociological theory. Complex features have long been articulated in sociological theorization, and sociology embraces the complexity principles of NESS through its growing attention to complex adaptive systems and non-equilibrium sciences, with human societies seen as highly complex, path-dependent, far-from equilibrium, and selforganising systems. In particular, Agent-BasedModelling provides a more coherent inclusion of NESS and complexity principles into sociology. Agent-based sociology uses data and statistics to gauge the ?generative sufficiency? of a given microspecification by testing the agreement between ?real-world? and computer generated macrostructures.When the model cannot generate the outcome to be explained, the microspecification is not a viable candidate explanation. The separation between the explanatory and pragmatic aspects of social science has led sociologists to be highly critical about the implementation of social science in policy. However, ABM allows systematic exploration of the consequences of modelling assumptions and makes it possible to model much more complex phenomena than previously. ABM has proved particularly useful in representing socio-technical and socio-ecological systems, with the potential to be of use in policy. ABM offers formalized knowledge that can appear familiar to policymakers versed in the methods and language of economics, with the prospect of sociology becoming more influential in policy.
Gilbert GN (1975) The development of science and scientific knowledge: a case study,
ARBER S, GILBERT N (1989) MEN - THE FORGOTTEN CARERS, SOCIOLOGY-THE JOURNAL OF THE BRITISH SOCIOLOGICAL ASSOCIATION 23 (1) pp. 111-118 BRITISH SOCIOLOGICAL ASSOC
Gilbert N (2004) Open problems in using agent-based models in industrial and labor dynamics, In: Leombruni R, Richiardi M (eds.), Industry and Labor Dynamics: the agent-based computational approach pp. 401-405 World Scientific
Gilbert GN (1994) Simulating social dynamics, In: Faulbaum F (eds.), Advances in Statistical Software 4 pp. 153-160 Gustav Fischer
MULKAY M, GILBERT GN (1983) SCIENTISTS THEORY TALK, CANADIAN JOURNAL OF SOCIOLOGY-CAHIERS CANADIENS DE SOCIOLOGIE 8 (2) pp. 179-197 UNIV ALBERTA
Gilbert GN (1987) Advice, discourse and explanations, In: Gilbert GN (eds.), Proceedings of the third workshop of the Alvey Explanation SIG Institute of Electrical Engineers
Jirotka M, Luff P, Gilbert GN (1991) Participation frameworks for computer mediated communication,
Gilbert GN (1996) Simulation as a research strategy, In: Troitzsch KG, Mueller U, Gilbert GN, Doran JE (eds.), Social science microsimulation pp. 448-454 Springer
McGlashan S, Bilange E, Fraser N, Heisterkamp P, Gilbert GN (1992) Dialogue Management for Telephone Information Systems,
Evandrou M, Arber S, Dale A, Gilbert GN (1986) Who cares for the elderly? Family care provision and receipt of statutory service, In: Philipson C, Bernard M, Strang P (eds.), Dependency and interdependency in old age: theoretical perspectives and policy alternatives Croom Helm
Gilbert GN, Luff P (1987) Interaction discourse and text generation in expert system interfaces, pp. 34-39 Institute of Electrical Engineers
Gilbert N (2002) Varieties of emergence, pp. 41-56 University of Chicago and Argonne National Laboratory
Hare M, Gilbert N, Maltby S, Pahl-Wostl C (2002) An internet-based role playing game for developing stakeholders' strategies for sustainable water management: experiences and comparisons with face-to-face gaming,
Fraser N, Gilbert GN (1991) Simulating speech systems, Computer Speech and Language 5 pp. 81-99
Gilbert GN, Jirotka M (1990) Planning procedural advice, Interacting with Computers 2 (3) pp. 313-329
Wooffitt RC, Fraser N, Gilbert N, McGlashan S (1997) Humans, computers and wizards: Studying human (simulated) computer interaction, Routledge
Gilbert N (2000) Models, processes and algorithms: towards a simulation toolkit, In: Suleiman R, Troitzsch KG, Gilbert N (eds.), Tools and Techniques for Social Science Simulation pp. 3-17 Physica-Verlag
Gilbert GN (1977) SAMP: a computer program for teaching survey sampling, Distributed by CONDUIT, University of Iowa.
Yang L, Gilbert N (2007) Case-based model of emotional expression influence on work group socialization and performance, ADVANCING SOCIAL SIMULATION: THE FIRST WORLD CONGRESS pp. 343-354 SPRINGER-VERLAG BERLIN
Bamford C, Dale A, Arber S, Gilbert GN (1987) Time series analysis of the General Household Survey, GHS Newsletter (3) pp. 15-17
Hassan S, Antunes L, Pavon J, Gilbert GN (2008) Stepping on Earth: A Roadmap for Data-driven Agent-Based Modelling., Proceedings of the 5th Conference of the European Social Simulation Association (ESSA08).
Arber S, Gilbert GN (1991) Women and working lives: divisions and change, Macmillan
Gilbert GN, Conte R (1995) Artificial Societies: the computer simulation of social life, UCL Press
Watts C, Gilbert N (2011) Does cumulative advantage affect collective learning in science? An agent-based simulation, Scientometrics 89 (1) pp. 437-463 Springer
Agent-based simulation can model simple micro-level mechanisms capable of generating macro-level patterns, such as frequency distributions and network structures found in bibliometric data. Agent-based simulations of organisational learning have provided analogies for collective problem solving by boundedly rational agents employing heuristics. This paper brings these two areas together in one model of knowledge seeking through scientific publication. It describes a computer simulation in which academic papers are generated with authors, references, contents, and an extrinsic value, and must pass through peer review to become published. We demonstrate that the model can fit bibliometric data for a token journal, Research Policy. Different practices for generating authors and references produce different distributions of papers per author and citations per paper, including the scale-free distributions typical of cumulative advantage processes. We also demonstrate the model?s ability to simulate collective learning or problem solving, for which we use Kauffman?s NK fitness landscape. The model provides evidence that those practices leading to cumulative advantage in citations, that is, papers with many citations becoming even more cited, do not improve scientists? ability to find good solutions to scientific problems, compared to those practices that ignore past citations. By contrast, what does make a difference is referring only to publications that have successfully passed peer review. Citation practice is one of many issues that a simulation model of science can address when the data-rich literature on scientometrics is connected to the analogy-rich literature on organisations and heuristic search.
Gilbert GN (1985) Decision support in large organisations, Data processing 27 pp. 28-30
Gilbert N, Jager W, Deffuant G, Adjali I (2007) Complexities in markets: Introduction to the special issue, JOURNAL OF BUSINESS RESEARCH 60 (8) pp. 813-815 ELSEVIER SCIENCE INC
Gilbert GN (1988) Using computers in teaching sociology, ESRC Data Archive Bulletin (40) pp. S2-S3
Gilbert GN, Mulkay M (1984) Opening Pandora?s Box: a sociological analysis of scientists' discourse, Cambridge University Press
Gilbert N, Ahrweiler P, Pyka A (2007) Learning in innovation networks: Some simulation experiments, Physica A 378 pp. 100-109
Gilbert N (2007) Special Issue: Complexities in Markets, Elsevier
GILBERT GN (1976) TRANSFORMATION OF RESEARCH FINDINGS INTO SCIENTIFIC KNOWLEDGE, SOCIAL STUDIES OF SCIENCE 6 (3-4) pp. 281-306 SAGE PUBLICATIONS LTD
Gilbert GN (1976) The development of science and scientific knowledge: the case of radar meteor research, In: Lemaine G, MacLeod R, Mulkay M, P Weingard (eds.), Perspectives on the emergence of Scientific Disciplines pp. 187-206 Mouton
Gilbert N, Schuster S, Besten MD, Yang L (2005) Environment design for emerging artificial societies,
Gilbert GN (1990) Sundial Dialogue Manager Functional Specification, Logica (Cambridge) Ltd
Ahrweiler P, Schilperoord M, Pyka A, Gilbert N (2014) Testing policy options for Horizon 2020 with SKIN, Understanding Complex Systems pp. 155-183 Springer
This chapter is about a SKIN application to the world of EU-funded research networks in the area of information and communication technologies (ICT). The application was commissioned by the DG Information Society and Media (DG INFSO) as an impact assessment of the funding strategies in the 7th Framework Programme (FP7) and ex-ante evaluation of the upcoming funding cycle called Horizon 2020. The focus of this chapter is on the changes of the SKIN model to become SKIN-INFSO, the strategy to calibrate the adapted SKIN model with empirical data from the European Commission to achieve realistic simulation results, and the ways we analysed and validated our results using network analysis. Details of the policy experiments using the SKIN-INFSO application for the study and their results are reported elsewhere [Ahrweiler, Gilbert, Pyka, Innovation policy modelling with SKIN. In: Johnston E et al (eds) Policy informatics. MIT Press, Cambridge, 2014, forthcoming]. © 2014 Springer-Verlag Berlin Heidelberg.
Chattoe E, Gilbert N (2001) Understanding consumption: What interviews with retired households can reveal about budgetary decisions, SOCIOLOGICAL RESEARCH ONLINE 6 (3) pp. U81-U97 SAGE PUBLICATIONS LTD
Frohlich DM, Crossfield LP, Gilbert GN (1985) Requirements for an intelligent form-filling interface, In: Johnson P, Cook S (eds.), People and computers: designing the interface pp. 102-117 Cambridge University Press
Salgado M, Marchione E, Gilbert N (2014) Analysing differential school effectiveness through multilevel and agent-based modelling, Journal of Artificial Societies and Social Simulation 17 (4) 3 University of Surrey
During the last thirty years education researchers have developed models for judging the comparative performance of schools, in studies of what has become known as ?differential school effectiveness?. A great deal of empirical research has been carried out to understand why differences between schools might emerge, with variable-based models being the preferred research tool. The use of more explanatory models such as agent-based models (ABM) has been limited. This paper describes an ABM that addresses this topic, using data from the London Educational Authority's Junior Project. To compare the results and performance with more traditional modelling techniques, the same data are also fitted to a multilevel model (MLM), one of the preferred variable-based models used in the field. The paper reports the results of both models and compares their performances in terms of predictive and explanatory power. Although the fitted MLM outperforms the proposed ABM, the latter still offers a reasonable fit and provides a causal mechanism to explain differences in the identified school performances that is absent in the MLM. Since MLM and ABM stress different aspects, rather than conflicting they are compatible methods.
Marchione E, Salgado M, Gilbert N (2010) 'What did you say?' Emergent communication in a multi-agent spatial configuration, ADVANCES IN COMPLEX SYSTEMS 13 (4) pp. 469-482 WORLD SCIENTIFIC PUBL CO PTE LTD
This paper reports the results of a multi-agent simulation designed to study the emergence and evolution of symbolic communication. The novelty of this model is that it considers some interactional and spatial constraints to this process that have been disregarded by previous research. The model is used to give an account of the implications of differences in the agents' behavior, which are embodied in a spatial environment. Two communicational dimensions are identified: the frequency with which agents refer to different topics over time and the spatial limitations on reaching recipients. We use the model to point out some interesting emergent communicational properties when the agents' behavior is altered by considering those two dimensions. We show the group of agents able to reach more recipients and less prone to changing the topic have the highest likelihood of driving the emergence and evolution of symbolic communication.
Yang L, Gilbert N (2007) Case-Based Model of Emotional Expression Influence on Work Group Socialization and Performance, In: Takahashi S, Sallach D, Rouchier J (eds.), Advancing Social Simulation pp. 343-353 Springer
Fielding J, Gilbert N (2000) Understanding Social Statistics, Sage
Yang L, Gilbert N (2007) Getting away from numbers: Using qualitative observation for agent-based modeling, pp. 175-185 World Scientific Publ Co Pte Ltd
Although in many social sciences there is a radical division between studies based on quantitative ( e. g. statistical) and qualitative ( e. g. ethnographic) methodologies and their associated epistemological commitments, agent-based simulation fits into neither camp, and should be capable of modelling both quantitative and qualitative data. Nevertheless, most agent-based models (ABMs) are founded on quantitative data. This paper explores some of the methodological and practical problems involved in basing an ABM on qualitative participant observation and proposes some advice for modelers.
Scholz R, Nokkala T, Pyka A, Ahrweiler P, Gilbert N (2009) Simulating European Union R&D policy - Knowledge dynamics in EU-funded innovation networks, Conference Proceedings - 6th Conference of the European Social Simulation Association, ESSA 2009
This paper discusses an agent-based simulation describing the science landscape in the European Union. The model focuses on the network structures resulting from the research cooperations of the actors participating in the European Framework Programms (FP). The paper presents the empirical data based on which the model is developed, and shows the internal structure of the simulation, including the simulation cycle of the agents and their operational background. Furthermore it discusses the results of the model by means of a standardised scenario, which is compared to the real FP's networks, and a policy driven experiment, which shows the potential of the model.
Gilbert N (2000) Modelling sociality: the view from Europe, In: Kohler T, Gumerman G (eds.), Dynamics in Human and Primate Societies: Agent-Based Modeling of Social and Spatial Processes pp. 355-372 Oxford University Press
The TELL ME simulation model is being developed to assist health authorities to understand the effects of their choices about how to communicate with citizens about protecting themselves from influenza epidemics. It will include an agent based model to simulate personal decisions to seek vaccination or adopt behaviour such as improved hand hygiene. This paper focusses on the design of the agents' decisions, using a combination of personal attitude, average local attitude, the local number of influenza cases and the case fatality rate. It also describes how personal decision making is connected to other parts of the model.
Gilbert GN (1983) In search of the action, In: Gilbert GN, Abell P (eds.), Accounts and Action pp. 8-34 Gower
Gilbert N (2007) Computational Social Science: Agent-based social simulation, In: Phan D, Amblard F (eds.), Agent-based Modelling and Simulation pp. 115-134 Bardwell
Gilbert GN, Wooffitt R (1994) Sociology in machines: applying sociology to software design, In: Woolgar S, Murray F (eds.), Social perspectives on software design MIT Press
Gilbert GN, Dale A, S.Arber, Evandrou M, Laczko F (1989) Resources in old age: ageing and the life course, In: Jeffreys M (eds.), Growing old in the 20th Century pp. 93-114 Routledge
Gilbert N, Troitzsch KG (1999) Simulation for the social scientist, Open University Press
Deffuant G, Gilbert N (2011) Preface, In: Deffuant G, Gilbert N (eds.), Viability and Resilience of Complex Systems 2011 pp. v-vii Springer
Gilbert N (2001) Research, Theory and Method, In: Researching Social Life Two Sage
Gilbert GN (1986) Proceedings of the 1st Alvey KBS Club Explanation Special Interest Group Workshop, Institute of Electrical Engineers.
Hamill L, Gilbert N (2015) Agent-Based Modelling in Economics, John Wiley & Sons
New methods of economic modelling have been sought as a result of the global economic downturn in 2008. This unique book highlights the benefits of an agent-based modelling (ABM) approach. It demonstrates how ABM can easily handle complexity: heterogeneous people, households and firms interacting dynamically. Unlike traditional methods, ABM does not require people or firms to optimise or economic systems to reach equilibrium. ABM offers a way to link micro foundations directly to the macro situation.
Key features:
" Introduces the concept of agent-based modelling and shows how it differs from existing approaches.
" Provides a theoretical and methodological rationale for using ABM in economics, along with practical advice on how to design and create the models.
" Starts each chapter with a short summary of the relevant economic theory and then shows how to apply ABM.
" Explores both topics covered in basic economics textbooks and current important policy themes; unemployment, exchange rates, banking and environmental issues.
" Describes the models in pseudocode, enabling the reader to develop programs in their chosen language.
" Is supported by a website featuring the NetLogo models described in the book.
Agent-based Modelling in Economics provides students and researchers with the skills to design, implement, and analyze agent-based models. Third year undergraduate, master and doctoral students, faculty and professional economists will find this book an invaluable resource.
Gilbert G, Hassan S, Antunes L, Pavon J Stepping on earth. A roadmap for data-driven agent-based modelling, Proceedings of European Social Simulation Association Annual Conference
Ankrah A, Frohlich DM, Gilbert GN (1990) Two ways to fill a bath, with and without knowing it, In: Proceedings of Interact ?90 pp. 73-78 Pitman
Gilbert GN (1988) The Alvey DHSS Demonstrator Project: applying IKBS to social security, In: Buchberger E, Göranzon B, Nygaard K (eds.), Artificial Intelligence: perspectives of AI as a social technology Tano
Ahrweiler P, Pyka A, Gilbert N (2011) A new model for university-industry links in knowledge-based economies, Journal of Product Innovation Management 28 (2) pp. 218-235
In this paper, we apply the agent-based SKIN model (Simulating Knowledge Dynamics in Innovation Networks) to university-industry links. The model builds on empirical research about innovation networks in knowledge-intensive industries with procedures relying on theoretical frameworks of innovation economics and economic sociology. Our experiments compare innovation networks with and without university agents. Results show that having universities in the co-operating population of actors raises the competence level of the whole population, increases the variety of knowledge among the firms, and increases innovation diffusion in terms of quantity and speed. Furthermore, firms interacting with universities are more attractive for other firms when new partnerships are considered. These results can be validated against empirical findings. The simulation confirms that university-industry links improve the conditions for innovation diffusion and enhance collaborative arrangements in innovation networks. © 2011 Product Development & Management Association.
Pyka A, Gilbert N, Ahrweiler P (2007) Simulating knowledge-generation and distribution processes in innovation collaborations and networks, CYBERNETICS AND SYSTEMS 38 (7) pp. 667-693 TAYLOR & FRANCIS INC
Buckland S, Cordingley ES, Frolich DM, Gilbert GN, Luff P (1987) Initial requirements specification for the Advice System, 19 University of Surrey
Arber S, Rajan L, Gilbert GN, Dale A (1985) Gender and Inequality in Britain, Longmans Educational Publishing
Conte R, Bonelli G, Gilbert N, Cioffi-Revilla C, Deffuant G, Kertesz J, Loreto V, Moat S, Nadal J-P, Sanchez A, Nowak A, Flache A, San Miguel M, Helbing D (2012) Manifesto of computational social science, European Physical Journal: Special Topics 214 (1) pp. 325-346 Springer Verlag
The increasing integration of technology into our lives has created unprecedented volumes of data on society's everyday behaviour. Such data opens up exciting new opportunities to work towards a quantitative understanding of our complex social systems, within the realms of a new discipline known as Computational Social Science. Against a background of financial crises, riots and international epidemics, the urgent need for a greater comprehension of the complexity of our interconnected global society and an ability to apply such insights in policy decisions is clear. This manifesto outlines the objectives of this new scientific direction, considering the challenges involved in it, and the extensive impact on science, technology and society that the success of this endeavour is likely to bring about. © The Author(s) 2012.
Doran J, Gilbert GN (1994) Simulating societies: an introduction, In: Gilbert GN, Doran J (eds.), Simulating Societies: the computer simulation of social phenomena UCL Press
Gilbert N, Jager W, Deffuant G, Adjali I (2007) Complexities in markets: introduction to the special issue, Journal of Business Research 60 pp. 813-815
Sholz R, Nokkala T, Ahrweiler P, Pyka A, Gilbert GN (2010) The agent-based NEMO model (SKEIN): simulating European Framework Programmes., In: Ahrweiler P (eds.), Innovation in Complex Social Systems pp. 300-314 Routledge, Taylor & Francis Group
Its approach opens up a new paradigm for innovation research, making innovationunderstandable and tractable using tools such as computational network analysis ...
Gilbert GN, Doran J (1994) Simulating Societies: the computer simulation of social phenomena, UCL Press
Gilbert GN, Luff P, Crossfield L, Frohlich DM (1987) A mixed initiative interface for expert systems: the Forms Helper,
Monk A, Gilbert GN, Nardi B, Mantei M, McCarthy J (1993) Mixing oil and water? Ethnography vs. experimental psychology in the study of computer-mediated communication, In: Proceedings of INTERCHI 1993 pp. 3-6 Association for Computing Machinery
Chattoe E, Gilbert N (1999) Talking about budgets: Time and uncertainty in household decision-making, Sociology 33 (1) pp. 85-103
Chattoe E, Gilbert N (1997) A simulation of adaptation mechanisms in budgetary decision-making, In: Conte R, Hegselmann, Terna P (eds.), Simulating social phenomena pp. 401-418 Springer
López-Sánchez M, Noria X, Rodríquez JA, Gilbert N, Shuster S (2004) Multi Agent Simulation Applied to On-line Music Distribution Market, pp. 151-154 IEEE Computer Society
Gilbert GN (1990) Support for members of the public, In: Bench-Capon T (eds.), Knowledge based systems and legal applications pp. 115-128 Academic
Gilbert GN (1996) Using Environmental Impact Assessments in the planning process, Global Environmental Change Programme
Conte R, Gilbert N, Sichman JS (1998) MAS and Social Simulation: A Suitable Commitment, In: Jaime S. Sichman, Rosaria Conte, Gilbert N (eds.), Lecture Notes in Computer Science pp. 1-9 Springer-Verlag
López-Sánchez M, Noria X, Rodríguez JA, Gilbert N (2005) Multi-Agent Based Simulation of News Digital Markets, International Journal of Computer Science & Applications 2 (1) pp. 7-14
Gilbert GN (1996) Holism, individualism and emergent properties: an approach from the perspective of simulation, In: Hegselmann R, Mueller U, Troitzsch KG (eds.), Modelling and simulation in the social sciences from the philosophy of science point of view pp. 1-12 Kluwer
Gilbert GN (1986) User models: can they be good enough?, Institute of Electical Engineers
Gilbert GN, Fraser N, Wooffitt R (1990) Organising computer talk, In: Luff P, Gilbert GN, Frohlich D (eds.), Computers and conversation pp. 235-258 Academic
Gilbert N (2005) Agent-based social simulation: dealing with complexity,
Gilbert GN, Buckland S, Frohlich D, Jirotka M, Luff P (1990) Providing advice through dialogue, pp. 301-307
López-Sánchez M, Noria X, Rodríquez-Aguilar JA, Gilbert N, Shuster S (2004) Simulation of Digital Content Distribution Using a Multi-Agent Simulation Approach, In: J. Vitria, Radeva P, Aguilo I (eds.), Recent Advances in Artificial Intelligence Research and Development pp. 341-348 IOS Press
Ahrweiler P, Gilbert N, Pyka A (2011) Agency and structure: a social simulation of knowledge-intensive industries, Computational and Mathematical Organization Theory 17 (1) pp. 59-76 SPRINGER
Modern knowledge-intensive economies are complex social systems where intertwining factors are responsible for the shaping of emerging industries: the self-organising interaction patterns and strategies of the individual actors (an agency-oriented pattern) and the institutional frameworks of different innovation systems (a structure-oriented pattern). In this paper, we examine the relative primacy of the two patterns in the development of innovation networks, and find that both are important. In order to investigate the relative significance of strategic decision making by innovation network actors and the roles played by national institutional settings, we use an agent-based model of knowledge-intensive innovation networks, SKIN. We experiment with the simulation of different actor strategies and different access conditions to capital in order to study the resulting effects on innovation performance and size of the industry. Our analysis suggests that actors are able to compensate for structural limitations through strategic collaborations. The implications for public policy are outlined.
Troitzsch K, Mueller U, Gilbert G, Doran J (1996) Social science microsimulation, Springer
Gilbert GN (1992) CSCW for real: reflections on experience, In: Diaper D, Sanger C (eds.), CSCW in Practice: an Introduction and Case Studies pp. 39-50 Springer-Verlag
Gilbert GN, Rajan L, Arber S, Dale A (1985) Class and Inequality in Britain, Longmans Educational Publishing
Gilbert GN (1993) SAMP: a survey sampling program, In: Middleton C (eds.), Sociology Teaching Handbook British Sociological Association
Gilbert GN (1992) Writing Sociology, In: Gilbert GN (eds.), Researching social life Sage
GILBERT GN (1977) REFERENCING AS PERSUASION, SOCIAL STUDIES OF SCIENCE 7 (1) pp. 113-122 SAGE PUBLICATIONS LTD
Gilbert GN (1983) Accounts and those accounts called actions, In: Gilbert GN, Abell P (eds.), Accounts and Action pp. 183-187 Gower
Gilbert GN, Fraser N (1991) Effects of system voice quality on user utterances in speech dialogue systems, pp. 57-60
Casnici N, Grimaldo F, Gilbert GN, Squazzoni F (2016) Attitudes of referees in a multidisciplinary journal: An empirical analysis, Journal of the Association for Information Science and Technology
This paper looks at 10 years of reviews in a multidisciplinary journal, The Journal of Artificial Societies and Social Simulation (JASSS), which is the flagship journal of social simulation. We measured referee behavior and referees' agreement. We found that the disciplinary background and the academic status of the referee have an influence on the report time, the type of recommendation and the acceptance of the reviewing task. Referees from the humanities tend to be more generous in their recommendations than other referees, especially economists and environmental scientists. Second, we found that senior researchers are harsher in their judgments than junior researchers, and the latter accept requests to review more often and are faster in reporting. Finally, we found that articles that had been refereed and recommended for publication by a multidisciplinary set of referees were subsequently more likely to receive citations than those that had been reviewed by referees from the same discipline. Our results show that common standards of evaluation can be established even in multidisciplinary communities.
Seel N, Gilbert GN, Morris ME (1990) A project-orientated view of CSCW, In: Proceedings of Interact ?90 pp. 903-908 Pitman
Asakawa T, Gilbert N (2003) Synthesizing experiences: lessons to be learned from internet-mediated simulation games, Simulation and gaming 34 (1) pp. 10-22
Roth C, Taraborelli D, Gilbert GN (2008) Démographie des communautés en ligne: le cas des wikis, Réseaux 26 (152) pp. 205-240
Les communautés eén ligne collaboratives ont connu un succés massif avec l?émergence des services et des plates-formes Web 2.0. Les wikis, et notamment la Wikipedia sont un des exemples les plus saillants de ce type de communautés de construction collective de contenus. La Wikipedia a á cet égard jusqu?ici concentré l?essentiel des efforts de recherche au sujet de ces communautés, même si l?ensemble des wikis constitue un écosystème possédant une très grande diversité de contenus, de populations, d?usages, de systèmes de gouvernance. Au contraire de la Wikipedia qui a probablement atteint la masse critique lui permettant d?être viable, la plupart des wikis luttent pour survivre et sont en compétition afin d?attirer contributeurs et articles de qualit é, connaissant ainsi des destinées variées, vertueuses ? croissance en population et en contenu ? ou fatales ? inactivité et vandalisme.
Gilbert GN (1989) Explanation as process, In: Filer N (eds.), Proceedings of the fourth workshop of the Alvey Explanation SIG Institute of Electrical Engineers
Gilbert GN (1993) Analyzing Tabular Data: loglinear and logistic models for social researchers, UCL Press
Cordingley E, Gilbert GN (1987) Alvey DHSS Demonstrator: advanced information technology for legislation based organisations and the public they serve, BURISA Newsletter (81) pp. 2-5
Deffuant G, Alvarez I, Barreteau O, Jabot F, Rougé C, de Vries B, Edmonds B, Gilbert N, Gotts N, Janssen S, Hilden M, Kolditz O, Murray-Rust D, Smits P (2012) Data and models for exploring sustainability of human well-being in global environmental change, European Physical Journal: Special Topics 214 (1) pp. 519-545 Springer Verlag
This position paper proposes a vision for the research activity about sustainability in global environmental change (GEC) taking place in the FuturICT flagship project. This activity will be organised in an "Exploratory", gathering a core network of European scientists from ICT, social simulation, complex systems, economics, demographics, Earth system science. These research teams will collaborate in building a self-organising network of data sources and models about GEC and in using new facilities fostering stakeholder participation. We develop examples of concrete directions for this research: world wide virtual population with demographic and some economic descriptors, ecosystem services production and distribution, governance systems at various scales. © EDP Sciences, Springer-Verlag 2012.
Gilbert GN (1995) Using computer simulation to study social phenomena, Bulletin de Methodologie Sociologique (47) pp. 99-111
Gilbert G, Ahrweiler P, Pyka A (2010) Learning in innovation networks: Some simulation experiments, In: Ahrweiler P (eds.), Innovation in Complex Social Systems (16) pp. 235-249 Routledge, Taylor & Francis
According to the organizational learning literature, the greatest competitive advantage a firm has is its ability to learn. In this paper, a framework for modeling learning competence in firms is presented to improve the understanding of managing innovation. Firms with different knowledge stocks attempt to improve their economic performance by engaging in radical or incremental innovation activities and through partnerships and networking with other firms. In trying to vary and/or to stabilize their knowledge stocks by organizational learning, they attempt to adapt to environmental requirements while the market strongly selects on the results. The simulation experiments show the impact of different learning activities, underlining the importance of innovation and learning. This chapter is a reprint of an article published as Gilbert, GN, Ahrweiler, P. & Pyka, A. (2007). Learning in innovation networks: Some simulation experiments. Physica A, 378 (1): 100?109 DOI:10.1016/j.physa.2006.11.050. Available online at: http://www.sciencedirect.com/science/article/pii/S0378437106012714
Gilbert GN (1995) Policy Instruments for Environmental Regulation, The Globe (26) pp. 8-10
Ahrweiler P, Gilbert N (2005) Caffè Nero: the Evaluation of Social Simulation, Journal of Artificial Societies and Social Simulation 8 (4) pp. http-//jasss.soc.surrey.ac.uk/8/4/14.html
This contribution deals with the assessment of the quality of a simulation by discussing and comparing "real-world" and scientific social simulations. We use the example of the Caffè Nero in Guildford as a 'real-world' simulation of a Venetian café. The construction of everyday simulations like Caffè Nero has some resemblance to the construction procedure of scientific social simulations. In both cases, we build models from a target by reducing the characteristics of the latter sufficiently for the purpose at hand; in each case, we want something from the model we cannot achieve easily from the target. After briefly discussing the 'ordinary' method of evaluating simulations called the 'standard view' and its adversary, a constructivist approach asserting that 'anything goes', we heed these similarities in the construction process and apply evaluation methods typically used for everyday simulations to scientific simulation and vice versa. The discussion shows that a 'user community view' creates the foundation for every evaluation approach: when evaluating the Caffè Nero simulation, we refer to the expert community (customers, owners) who use the simulation to get from it what they would expect to get from the target; similarly, for science, the foundation of every validity discussion is the ordinary everyday interaction that creates an area of shared meanings and expectations. Therefore, the evaluation of a simulation is guided by the expectations, anticipations and experience of the community that uses it ? for practical purposes (Caffè Nero), or for intellectual understanding and for building new knowledge (science simulation).
MARCHIONE ELIO, SALGADO MAURICIO, GILBERT NIGEL (2010) 'WHAT DID YOU SAY?' EMERGENT COMMUNICATION IN A MULTI-AGENT SPATIAL CONFIGURATION, Advances in Complex Systems 13 (04) pp. 469-482
This paper reports the results of a multi-agent simulation designed to study the emergence and evolution of symbolic communication. The novelty of this model is that it considers some interactional and spatial constraints to this process that have been disregarded by previous research. The model is used to give an account of the implications of differences in the agents' behavior, which are embodied in a spatial environment. Two communicational dimensions are identified: the frequency with which agents refer to different topics over time and the spatial limitations on reaching recipients. We use the model to point out some interesting emergent communicational properties when the agents' behavior is altered by considering those two dimensions. We show the group of agents able to reach more recipients and less prone to changing the topic have the highest likelihood of driving the emergence and evolution of symbolic communication.
Gilbert GN, Crossfield L (1986) Introducing expert systems into a large legislation-based organisation, In: T. Bernold (eds.), Expert Systems and Knowledge Engineering pp. 95-100 North-Holland
Elsenbroich C, Gilbert N (2013) Modelling Norms, Springer
The book focusses on questions of individual and collective action, the emergence and dynamics of social norms and the feedback between individual behaviour and social phenomena. It discusses traditional modelling approaches to social norms and shows the usefulness of agent-based modelling for the study of these micro-macro interactions. Existing agent-based models of social norms are discussed and it is shown that so far too much priority has been given to parsimonious models and questions of the emergence of norms, with many aspects of social norms, such as norm-change, not being modelled. Juvenile delinquency, group radicalisation and moral decision making are used as case studies for agent-based models of collective action extending existing models by providing an embedding into social networks, social influence via argumentation and a causal action theory of moral decision making. The major contribution of the book is to highlight the multifaceted nature of the dynamics of social norms, consisting not only of emergence, and the importance of embedding of agent-based models into existing theory.
Gilbert N (2007) Dilemmas of privacy and surveillance: challenges of technological change, Criminal Justice Matters (68) pp. 41-42
ARBER S, GILBERT GN, DALE A (1985) PAID EMPLOYMENT AND WOMENS HEALTH - A BENEFIT OR A SOURCE OF ROLE STRAIN, SOCIOLOGY OF HEALTH & ILLNESS 7 (3) pp. 375-400 BLACKWELL PUBL LTD
Ahrweiler P, Gilbert N (1998) Computer Simulations in Science and Technology Studies, Springer
Matthews RB, Polhill JG, Gilbert N, Roach A (2005) Integrating agent-based social models and biophysical models, MODSIM05 - International Congress on Modelling and Simulation: Advances and Applications for Management and Decision Making, Proceedings pp. 1617-1623
Spatially and temporally explicit simulation modelling of natural resource management systems provides a framework to draw together in a mathematically unambiguous manner a wealth of information, and, as such, allows rigorous testing of hypotheses of how such systems can be changed, without the time, expense and moral implications of altering a real system. In recent years, a large number of integrated assessment models linking the human and biophysical components of particular systems have been developed to address this need, but in many of these models the human dimension is based on economic cost-benefit principles that attempt to optimise use of resources such as capital or labour to maximise a particular output. Limitations to these approaches are that they are structured to represent an equilibrium when production has stabilised, they presuppose a 'goal' of the system, and do not adequately consider the microdecisions being made by the various actors within it. Agent-based modelling (ABM) is an approach that has been receiving attention in recent years as a way of linking the biophysical and socioeconomic characteristics of a system, and which provides a way of addressing these limitations. ABM has aroused the interest of environmental modellers, mainly because it offers a way of incorporating the influence of human decision-making on the environment in a mechanistic and spatially explicit way, taking into account social interaction, adaptation, and multiple scales of decision-making. Several such models are now beginning to appear, many of which involve the grafting of an ABM representing a number of households onto a cellular automata 'landscape', with each agent being linked in some way to the cells over which it has influence. Apart from changes in actual land cover, however, these models generally treat the landscape as a relatively static entity, and do not simulate processes such as soil water and nutrient dynamics. The ones that do include such processes, do so somewhat simplistically. There is a need, therefore, to integrate dynamic biophysical simulation models with these emerging agent-based social simulation models. Different approaches to integrating such models are recognised - one such scheme refers to 'loosely-coupled', 'closely-coupled', and 'fully integrated' levels of integration. Loose- and closely-coupled models exchange driving variables between them, with closely-coupled models sharing common subprocesses, meaning that temporal
Gilbert G, Ahrweiler P (2009) The epistemologies of social simulation research, In: Squazzoni F (eds.), Epistemological aspects of computer simulation in the social sciences pp. 12-28
Ahrweiler P, Pyka A, Gilbert Nigel (2015) Policy Modelling of Large-Scale Social Systems: Lessons from the SKIN model of Innovation, In: Johnston E (eds.), Governance in the Information Era: Theory and Practice of Policy Informatics (13) 13 pp. 229-246 Routledge, Taylor & Francis Group
Rowden J, Lloyd DJB, Gilbert N (2014) A model of political voting behaviours across different countries, Physica A: Statistical Mechanics and its Applications 413 pp. 609-625
This paper analyses, models mathematically, and compares national voting behaviours across seven democratic countries that have a long term election history, focusing on re-election rates, leaders' reputation with voters and the importance of friends' and family influence. Based on the data, we build a Markov model to test and explore national voting behaviour, showing voters are only influenced by the most recent past election. The seven countries can be divided into those in which there is a high probability that leaders will be re-elected and those in which incumbents have relatively less success. A simple stochastic phenomenological dynamical model of electoral districts in which voters may be influenced by social neighbours, political parties and political leaders is then created to explore differences in voter behaviours in the countries. This model supports the thesis that an unsuccessful leader has a greater negative influence on individual voters than a successful leader, while also highlighting that increasing the influence on voters of social neighbours leads to a decrease in the average re-election rate of leaders, but raises the average amount of time the dominant party is in charge.© 2014 Elsevier B.V. All rights reserved.
Gilbert GN (1989) Explanation and dialogue, Knowledge Engineering Review 4 pp. 235-247
Jirotka M, Gilbert GN, Luff P (1992) On the social organisation of organisations, International Journal of Computer Supported Cooperative Work 1 (1) pp. 95-118
Roth C, Taraborelli D, Gilbert N (2008) Measuring Wiki viability: An empirical assessment of the social dynamics of a large sample of Wikis, WikiSym 2008 - The 4th International Symposium on Wikis, Proceedings
This paper assesses the content- and population-dynamics of a large sample of wikis, over a timespan of several months, in order to identify basic features that may predict or induce different types of fate. We analyze and discuss, in particular, the correlation of various macroscopic indicators, structural features and governance policies with wiki growth patterns. While recent analyses of wiki dynamics have mostly focused on popular projects such as Wikipe-dia, we suggest research directions towards a more general theory of the dynamics of such communities. © 2008 ACM.
Watts C, Gilbert N (2014) Simulating innovation: Comparing models of collective knowledge, technological evolution and emergent innovation networks, Advances in Intelligent Systems and Computing 229 AISC pp. 189-200
Computer simulation models have been proposed as a tool for understanding innovation, including models of organisational learning, technological evolution, knowledge dynamics and the emergence of innovation networks. By representing micro-level interactions they provide insight into the mechanisms by which are generated various stylised facts about innovation phenomena. This paper summarises work carried out as part of the SIMIAN project and to be covered in more detail in a forthcoming book. A critical review of existing innovation- related models is performed. Models compared include a model of collective learning in networks [1], a model of technological evolution based around percolation on a grid [2, 3], a model of technological evolution that uses Boolean logic gate designs [4], the SKIN model [5], a model of emergent innovation networks [6], and the hypercycles model of economic production [7]. The models are compared for the ways they represent knowledge and/or technologies, how novelty enters the system, the degree to which they represent open-ended systems, their use of networks, landscapes and other pre-defined structures, and the patterns that emerge from their operations, including networks and scale-free frequency distributions. Suggestions are then made as to what features future innovation models might contain. © Springer-Verlag Berlin Heidelberg 2014.
Gilbert GN (1996) Environments and languages to support social simulation, In: Troitzsch KG, Mueller U, Gilbert GN, Doran JE (eds.), Social science microsimulation pp. 457-459 Springer
Gilbert GN (1990) Claimant Information Systems, In: Bench-Capon T (eds.), Knowledge based systems and legal applications pp. 183-198 Academic
Gilbert GN, Mulkay MJ (1980) Contexts of scientific discourse: social accounting in experimental papers, In: Knorr KD, Krohn R, Whitley R (eds.), The social process of scientific investigation pp. 269-296 Reidel
Gilbert N (1999) Simulation: a new way of doing social science, American Behavioral Scientist 40 (10) pp. 1485-1487
Gilbert GN (1987) Proceedings of the 3rd Alvey KBS Club Explanation Special Interest Group Workshop, Institute of Electrical Engineers.
Gilbert GN (1991) Artificial Societies, University of Surrey
Gilbert N (2007) A generic model of collectivities, CYBERNETICS AND SYSTEMS 38 (7) pp. 695-706 TAYLOR & FRANCIS INC
Suleiman R, Troitzsch KG, Gilbert N (2000) Tools and Techniques for Social Science Simulation, Physica-Verlag
Gilbert N, Dresner S (2001) The dynamics of European science and technology policies, Ashgate
Dale A, Gilbert GN (1985) Scientific Information Retrieval, ESRC Software Bulletin (13) pp. 1-2
Gilbert N (1997) A simulation of the structure of academic science, Sociological Research Online 2 (2) pp. http-//www.socresonline.org.uk/socresonline/2/2/3.html
MULKAY M, GILBERT GN (1986) REPLICATION AND MERE REPLICATION, PHILOSOPHY OF THE SOCIAL SCIENCES 16 (1) pp. 21-37 SAGE PUBLICATIONS INC
Gilbert GN (1981) Modelling society: an introduction to loglinear analysis for social researchers, Allen and Unwin
Hewitt B, Gilbert GN (1992) Group interfaces, In: Diaper D, Sanger C (eds.), CSCW in Practice: an Introduction and Case Studies pp. 31-38 Springer-Verlag
Dale A, Arber S, Gilbert GN (1983) Alternative measures of social class for women and families, Equal Opportunities Commission
Monk AF, Gilbert N (1995) Perspectives on HCI: Diverse Approaches, Academic Press
Fielding JL, Gilbert GN (2006) Understanding social statistics, Sage Publications Ltd
The book is full of up-to-date examples and useful and clear illustrations using the latest SPSS software.
Gilbert GN (1980) Being interviewed: a rôle analysis, Social Science Information 19 pp. 227-236.
Gilbert N, Ahrweiler P (2009) The epistemologies of social simulation research, Lecture Notes in Computer Science (Revised Selected and Invited Papers) 5466 pp. 12-28 Springer
What is the best method for doing simulation research? This has been the basis of a continuing debate within the social science research community. Resolving it is important if the community is to demonstrate clearly that simulation is an effective method for research in the social sciences. In this paper, we tackle the question from a historical and philosophical perspective. We argue that the debate within social simulation has many connections with the debates that have echoed down the years within the wider social science community about the character of social science knowledge and the appropriate epistemological and methodological assumptions on which social science research should rest. © Springer-Verlag Berlin Heidelberg 2009.
Gilbert N (2005) Quality, Quantity and the Third Way, In: Holland J, Campbell J (eds.), Methods in Development Research: Combining Qualitative and Quantitative Approaches pp. 141-148 ITDG Publishing
Mulkay MJ, Gilbert GN (1982) What is the Ultimate Question? Some Remarks in Defence of the Analysis of Scientific Discourse, Social Studies of Science 12 (2) pp. 309-319
Arber S, Gilbert GN (1991) Re-assessing women's working lives: an introductory essay, In: Arber S, Gilbert GN (eds.), Women and working lives: divisions and change Macmillan
Elsenbroich C, Anzola D, Gilbert GN (2016) Social Dimensions of Organised Crime: Modelling the Dynamics of Extortion Rackets, Springer International Publishing AG
This book presents a multi-disciplinary investigation into extortion rackets with a particular focus on the structures of criminal organisations and their collapse, societal processes in which extortion rackets strive and fail and the impacts of bottom-up and top-down ways of fighting extortion racketeering. Through integrating a range of disciplines and methods the book provides an extensive case study of empirically based computational social science. It is based on a wealth of qualitative data regarding multiple extortion rackets, such as the Sicilian Mafia, an international money laundering organisation and a predatory extortion case in Germany. Computational methods are used for data analysis, to help in operationalising data for use in agent-based models and to explore structures and dynamics of extortion racketeering through simulations. In addition to textual data sources, stakeholders and experts are extensively involved, providing narratives for analysis and qualitative validation of models. The book presents a systematic application of computational social science methods to the substantive area of extortion racketeering. The reader will gain a deep understanding of extortion rackets, in particular their entrenchment in society and processes supporting and undermining extortion rackets. Also covered are computational social science methods, in particular computationally assisted text analysis and agent-based modelling, and the integration of empirical, theoretical and computational social science.
Gilbert GN (1992) Research, theory and method, In: Gilbert GN (eds.), Researching social life Sage
Gilbert GN (1988) Forms of explanation, pp. 72-75
Balke T, Gilbert N (2014) How do agents make decisions? A survey, Journal of Artificial Societies and Social Simulation 17 (4) pp. 1-1 University of Surrey
When designing an agent-based simulation, an important question to answer is how to model the decision making processes of the agents in the system. A large number of agent decision making models can be found in the literature, each inspired by different aims and research questions. In this paper we provide a review of 14 agent decision making architectures that have attracted interest. They range from production-rule systems to psychologically- and neurologically-inspired approaches. For each of the architectures we give an overview of its design, highlight research questions that have been answered with its help and outline the reasons for the choice of the decision making model provided by the originators. Our goal is to provide guidelines about what kind of agent decision making model, with which level of simplicity or complexity, to use for which kind of research question.
GILBERT GN (1989) Book Review of Shaping Written Knowledge: The Genre and Activity of the Experimental Article in Science. Charles Bazerman, American Journal of Sociology 95 (3) pp. 811-812
Gilbert Nigel, Ahrweiler P (2015) The Quality of Social Simulation: an Example from Research Policy Modelling, In: Janssen M, Wimmer M, Deljoo A (eds.), Policy Practice and Digital Science ? Integrating Complex Systems, Social Simulation and Public Administration in Policy Research 10 pp. 35-55 Springer Internatinal Publishing
This contribution deals with the assessment of the quality of a simulation. The first section points out the problems of the Standard View and the Constructivist View in evaluating social simulations. A simulation is good when we get from it what we originally would have liked to get from the target; in this, the evaluation of the simulation is guided by the expectations, anticipations and experience of the community that uses it. This makes the user community view the most promising mechanism to assess the quality of a policy modelling exercise. The second section looks at a concrete policy modelling example to test this idea. It shows that the very first negotiation and discussion with the user community to identify their questions is highly user-driven, interactive, and iterative. It requires communicative skills, patience, willingness to compromise on both sides, and motivation to make the formal world of modellers and the narrative world of practical policymaking meet. Often, the user community is involved in providing data for calibrating the model. It is not an easy issue to confirm the existence, quality and availability of data and check for formats and database requirements. As the quality of the simulation in the eyes of the user will very much depend on the quality of the informing data and the quality of the model calibration, much time and effort need to be spent in coordinating this issue with the user community. Last but not least, the user community has to check the validity of simulation results and has to believe in their quality. Users have to be enabled to understand the model, to agree with its processes and ways to produce results, to judge similarity between empirical and simulated data etc. Although the User Community view might be the most promising, it is the most work-intensive mechanism to assess the quality of a simulation. Summarising, to trust the quality of a simulation means to trust the process that produced its results. This process includes not only the design and construction of the simulation model itself, but also the whole interaction between stakeholders, study team, model, and findings.
Yang L, Gilbert N (2008) Getting away from numbers: Using qualitative observation for agent-based modeling, ADVANCES IN COMPLEX SYSTEMS 11 (2) pp. 175-185 WORLD SCIENTIFIC PUBL CO PTE LTD
Gilbert GN, Pyka A, Ahrweiler P (2001) Innovation Networks - A Simulation Approach, Journal of Artificial Societies and Social Simulation 4 (3)
A multi-agent simulation embodying a theory of innovation networks has been built and used to suggest a number of policy-relevant conclusions. The simulation animates a model of innovation (the successful exploitation of new ideas) and this model is briefly described. Agents in the model representing firms, policy actors, research labs, etc. each have a knowledge base that they use to generate ?artefacts? that they hope will be innovations. The success of the artefacts is judged by an oracle that evaluates each artefact using a criterion that is not available to the agents. Agents are able to follow strategies to improve their artefacts either on their own (through incremental improvement or by radical changes), or by seeking partners to contribute additional knowledge. It is shown though experiments with the model's parameters that it is possible to reproduce qualitatively the characteristics of innovation networks in two sectors: personal and mobile communications and biotechnology.
Gilbert N (2006) Sciences sociales computationnelles: simulation sociale multi-agents, In: Amblard F, Phan D (eds.), Modélisation et simulation multi-agents: applications pour les Sciences de l'Homme et de la Société pp. 141-157 Lavoisier
Gilbert N, den Besten M, Bontovics A, Craenen BGW, Divina F, Eiben AE, Griffioen R, Hévízi G, Lõrincz A, Paechter B, Schuster S, Schut MC, Tzolov C, Vogt P, Yang L (2006) Emerging Artificial Societies Through Learning, Journal of Artificial Societies and Social Simulation 9 (2) pp. http-//jasss.soc.surrey.ac.uk/9/2/9.html
The NewTies project is implementing a simulation in which societies of agents are expected to de-velop autonomously as a result of individual, population and social learning. These societies are expected to be able to solve environmental challenges by acting collectively. The challenges are in-tended to be analogous to those faced by early, simple, small-scale human societies. This report on work in progress outlines the major features of the system as it is currently conceived within the project, including the design of the agents, the environment, the mechanism for the evolution of language and the peer-to-peer infrastructure on which the simulation runs.
Gilbert GN, S. Buckland, Dawson P, Frohlich D, Luff P, Crossfield L, Cordingley B, Robinson P (1988) Functional specification for the Advice System, 38 University of Surrey
Schuster S, Gilbert N (2005) Agent based simulation for modelling the distribution of online music, First International Conference on Automated Production of Cross Media Content for Multi-channel Distribution, Proceedings pp. 171-178 IEEE COMPUTER SOC
Fraser N, Gilbert GN, MacDermid C (1992) The value of simulation data,
GILBERT GN, MULKAY M (1984) EXPERIMENTS ARE THE KEY, PARTICIPANTS HISTORIES AND HISTORIANS HISTORIES OF SCIENCE, ISIS 75 (276) pp. 105-125 UNIV CHICAGO PRESS
Gilbert N (2000) The simulation of social processes, In: Coppock T (eds.), Information Technology and Scholarship pp. 203-216 Oxford University Press
Gilbert GN, Abell P (1983) Accounts and action, Gower
Gilbert N, Bullock S (2014) Complexity at the social science interface, Complexity 19 (6) pp. 1-4
This article introduces a special issue of Complexity dedicated to the increasingly important element of complexity science that engages with social policy. We introduce and frame an emerging research agenda that seeks to enhance social policy by working at the interface between the social sciences and the physical sciences (including mathematics and computer science), and term this research area the "social science interface" by analogy with research at the life sciences interface. We locate and exemplify the contribution of complexity science at this new interface before summarizing the contributions collected in this special issue and identifying some common themes that run through them. © 2014 Wiley Periodicals, Inc.
Gilbert N (1997) Centre for Research on Simulation in the Social Sciences, SOCIOLOGICAL RESEARCH ONLINE 2 (2) pp. U125-U126 SAGE PUBLICATIONS LTD
Gilbert N (2000) The simulation of social processes, In: Ferrand N (eds.), Modèles et Systèmes Multi-Agents pour la Gestion de l'Environment et des Territoires pp. 121-137 Cemagref Éditions
Harding S, Gilbert GN (1993) Negotiating the take up of Formal Methods, In: Quintas P (eds.), Social Dimensions of Systems Engineering: People, Processes, Policies and Software Development Ellis Horwood
Gilbert N (1995) Emergence in social simulation, In: Gilbert N, Conte R (eds.), Artificial Societies: the computer simulation of social life pp. 144-156 UCL Press
Burrows R, Gilbert GN, Pollert A (1991) Fordism and flexibility, In: Burrows R, Gilbert GN, Pollert A (eds.), Fordism and flexibility: divisions and change Macmillan
Mulkay MJ, Gilbert GN (1981) Putting Philosophy to Work: Karl Popper's Influence on Scientific Practice, Philosophy of the Social Sciences 11 (3) pp. 389-407
Gilbert N, Chattoe E (2001) Hunting the unicorn: an exploration of the simulation of small group leadership, In: Saam NJ, Schmidt B (eds.), Cooperative Agents: applications in the social sciences pp. 109-124 Kluwer
Roth C, Taraborelli D, Gilbert N (2011) Symposium on "Collective representations of quality", Mind and Society 10 (2) pp. 165-168 Springer Verlag
Collective representations of the quality of artifacts are produced by human societies in a variety of contexts. These representations of quality emerge from a broad range of social interactions, from the uncoordinated behaviour of large collectives of individuals, to the interaction between individuals and organizations, to complex socio-technical processes such as those enabled by online peer production systems. This special issue brings together contributions from sociology, social psychology and social simulation to shed light on the nature of these representations and the social processes that produce them.
Ahrweiler P, Schilperoord M, Gilbert N, Pyka A (2012) Simulating the Role of MNCs for Knowledge and Capital Dynamics in Networks of Innovation, In: Heidenreich M, von Ossietzky C (eds.), Innovation and Institutional Embeddedness of Multinational Companies 6 pp. 141-168 Edward Elgar Publishing
Gilbert GN, Maude TI, Heaton NO, Wilson PA, Marshall CJ (1984) An experiment in group working on mailbox systems, In: Interact ?84 IFIP conference on Human-Computer Interaction pp. 396-400 North-Holland
López-Sánchez M, Noria X, Rodríguez JA, Gilbert N (2004) Multi Agent Simulation Applied to Electronic News Distribution, pp. 7-11 16th European Conference on Artificial Intelligence
Doran J, Palmer M, Gilbert GN, Mellars P (1994) The EOS Project: modelling Upper Palaeolithic social change, In: Gilbert GN, Doran J (eds.), Simulating Societies: the computer simulation of social phenomena UCL Press
Gilbert N (2003) Societal Aspects of Risk, Royal Academy of Engineering
Gilbert N (2007) A generic model of collectivities, Cybernetics and Systems: An International Journal 38 (7) pp. 695-706
ARBER S, GILBERT GN, EVANDROU M (1988) GENDER, HOUSEHOLD COMPOSITION AND RECEIPT OF DOMICILIARY SERVICES BY ELDERLY DISABLED PEOPLE, JOURNAL OF SOCIAL POLICY 17 pp. 153-175 CAMBRIDGE UNIV PRESS
Gilbert N, Maltby S, Asakawa T (2002) Participatory simulations for developing scenarios in environmental resource management, In: Urban C (eds.), 3rd workshop on Agent-based simulation pp. 67-72 SCS-Europe
GILBERT GN (1978) SIMULATION APPROACH TO TEACHING SURVEY SAMPLING, TEACHING SOCIOLOGY 5 (3) pp. 287-294 AMER SOCIOLOGICAL ASSOC
Gilbert N, Hawksworth JC, Swinney PA (2009) An agent-based model of the English housing market, In: AAAI Spring Symposium - Technical Report SS-09-09 pp. 30-35
Gilbert N, Bankes S (2002) Platforms and Methods for Agent-based Modeling, Proceedings of the National Academy of Sciences of the USA 99 (supll.3) pp. 7197-7198
Ramanath AM, Gilbert N (2004) Techniques for the construction and evaluation of participatory simulations, Journal of Artificial Societies and Social Simulation 7 (4) pp. http-//jasss.soc.surrey.ac.uk/7/4/1.html
Paolucci M, Conte R, Bonelli G, Kossman D, Gross M, Koumoutsakos P, Krause A, Sorkine O, Helbing D, Lukowicz P, Slusallek P, Argyrakis P, Blandford A, Anderson S, de Freitas S, Edmonds B, Gilbert N, Kohlhammer J, Linnér B-O, Sumner RW (2012) Towards a living earth simulator, European Physical Journal: Special Topics 214 (1) pp. 77-108
The Living Earth Simulator (LES) is one of the core components of the FuturICT architecture. It will work as a federation of methods, tools, techniques and facilities supporting all of the FuturICT simulation-related activities to allow and encourage interactive exploration and understanding of societal issues. Society-relevant problems will be targeted by leaning on approaches based on complex systems theories and data science in tight interaction with the other components of FuturICT. The LES will evaluate and provide answers to realworld questions by taking into account multiple scenarios. It will build on present approaches such as agent-based simulation and modeling, multiscale modelling, statistical inference, and data mining, moving beyond disciplinary borders to achieve a new perspective on complex social systems. © The Author(s) 2012.
GILBERT GN, MULKAY M (1982) WARRANTING SCIENTIFIC BELIEF, SOCIAL STUDIES OF SCIENCE 12 (3) pp. 383-408 SAGE PUBLICATIONS LTD
Peters S, Gilbert N (1997) The electronic alternative: Sociological Research Online, LEARNED PUBLISHING 10 (4) pp. 339-343 ASSOC LEARNED PROFESSIONAL SOC PUBL
Schuster S, Gilbert N (2005) Agent Based Simulation for Modelling the Distribution of Online Music, pp. 171-178
Fielding J, Gilbert N (2005) Understanding Social Statistics, Sage
Gilbert N, Abbott A (2005) Special issue: Social science computation, pp. 859-1241 The University of Chicago Press
Hassan S, Pavon J, Antunes L, Gilbert GN (2010) Injecting Data into Agent-Based Simulation., In: Takadama K, Cioffi-Revilla C, Deffuant G (eds.), Simulating Interacting Agents and Social Phenomena pp. 173-185 Springer-Verlag New York Inc
Agent-based modeling and social simulation have emerged as both developments of and challenges to the social sciences.
Pyka A, Gilbert N, Ahrweiler P (2002) Simulating Innovation Networks, In: Pyka A, Küppers G (eds.), Innovation Networks: Theory and Practice Edward Elgar
Gilbert GN, Heath C (1986) Text, competence and logic: An exercise, Qualitative Sociology 9 (3) pp. 215-236
Professional medical practice, like other organizational conduct, relies upon records which document transactions between members and their clientele. Medical practitioners employ a set of conventions providing for the systematic recording and interpretation of medical record cards that forms a social organization underlying the records cards' ordinary usage. In this paper we examine these conventions and develop a computer program which captures elements of their structure and use. By doing so we illustrate one way in which sociological analysis can contribute to the design of ?intelligent systems.? We also suggest that the emerging discipline of Artificial Intelligence might find recent developments in sociology pertinent to its concerns.
Gilbert GN (1987) Proceedings of the 2nd Alvey KBS Club Explanation Special Interest Group Workshop, Institute of Electrical Engineers.
Gilbert GN, Arber S, Dale A, O?Byrne J (1984) Surrey GHS data sets, ESRC Data Archive Bulletin (27) pp. 5-6
An agent-based computational model, based on longitudinal ethnographic data about the dynamics of intra-group behaviour and work group performance, has been developed from observing an organizational group in the service sector. The model, in which the agents represent workers and tasks, is used to assess the effect of emotional expressions on the dynamics of interpersonal behaviour in work groups, particularly for groups that have recent newcomers. The model simulates the gradual socialization of newcomers into the work group. Through experimenting with the model, conclusions about the factors that influence the socialization process were studied in order to obtain a better understanding of the effect of emotional expressions. It is shown that although positive emotional display accelerates the socialization process, it can have negative effects on work group performance.
Mulkay MJ, Gilbert GN (1982) Accounting for Error: How Scientists Construct their Social World when they Account for Correct and Incorrect Belief, Sociology 16 (2) pp. 165-183
There is an asymmetry in the procedures used by natural scientists to account for `correct belief' and for `error'. Correct belief is treated as the normal state of affairs, as deriving unproblematically from experimental evidence, and as requiring no special explanation. Errors are seen as something to be explained away, as due to the intrusion of non-scientific influences. An elaborate repertoire of interpretative resources is employed in accounting for error. Asymmetrical accounting for error and for correct belief is a social device which reinforces the traditional conception of scientific rationality and which makes the community of scientists appear as the kind of community we, and they, recognize as scientific.
Gilbert GN, Woolgar S (1974) The quantitative study of science, Science Studies 4 pp. 279-294
Gilbert GN (1977) Growth and decline of a scientific specialty: The case of radar meteor research, EOS, Transactions Amercian Geophysical Union 58 (5) pp. 273-277
This article traces the rise and eventual decline of a field of research devoted to the study of meteors by radar. It shows how a new experimental tool, radar, provided the impetus for the emergence of a new scientific specialty, and how this specialty later declined after its initial problems had been solved and after most of its participants had moved on to more promising fields. Radar meteor research provides an example of how new fields grow and how scientific developments affect the research careers of scientists.
Gilbert N, Ahrweiler P (2006) The Epistemologies of Social Simulation Research, pp. 12-28 Springer-Verlag Berlin
What is the best method for doing simulation research? This has been the basis of a continuing debate within the social science research community. Resolving it is important if the community is to demonstrate clearly that simulation is an effective method for research in the social sciences. In this paper, we tackle the question from a historical and philosophical perspective. We argue that the debate within social simulation has many connections with the debates that have echoed down the years within the wider social science community about the character of social science knowledge and the appropriate epistemological and methodological assumptions on which social science research should rest.
GILBERT GN (1988) THE ALVEY DHSS DEMONSTRATOR PROJECT - APPLYING INTELLIGENT KNOWLEDGE-BASED SYSTEMS TO SOCIAL-SECURITY, INFORMATION AGE 10 (2) pp. 113-115 BUTTERWORTH-HEINEMANN LTD
Conte R, Gilbert N (1995) Computer simulation for social theory, In: Gilbert N, Conte R (eds.), Artificial Societies: the computer simulation of social life pp. 1-18 UCL Press
Gilbert N, Terna P (2000) How to build and use agent-based models in social science, Mind and Society 1 (1) pp. 57-72
Ahrweiler P, Pyka A, Gilbert N (2004) Simulating Knowledge Dynamics in Innovation Networks, In: Leombruni R, Richiardi M (eds.), Industry and Labor Dynamics: The Agent-based Computational Economics Approach pp. 284-296 World Scientific Press
Dresner S, Gilbert N (1999) Decision-making processes for projects requiring EIA: case studies in six European countries, Journal of Environmental Assessment Policy and Management 1 (1) pp. 105-130
Gilbert GN, Arber S, Dale A (1980) SPSS and the General Household Survey, SSRC Survey Archive Bulletin May
Gilbert GN (2000) Book Review of The computational beauty of nature: Computer explorations of fractals, chaos, complex systems and adaptation. Gary William Flake, JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION 3 (1) pp. 119-120 J A S S S
Vaux J, Gilbert N (2002) Innovation networks by design: the case of the Mobile VCE, In: Pyka A, Küppers G (eds.), Innovation networks: Theory and Practice Edward Elgar
Jordan J, Gilbert N (1999) Think local - act global: discourses of environment and local protest, In: Fairweather S (eds.), Environmental Futures pp. 39-53 Macmillan
Ahrweiler P, Schilperoord M, Pyka A, Gilbert GN (2015) Modelling Research Policy: Ex-Ante Evaluation of Complex Policy Instruments, Journal of Artificial Societies and Social Simulation 18 (4) pp. 5-5
This paper presents the agent-based model INFSO-SKIN, which provides ex-ante evaluation of possible funding policies in Horizon 2020 for the European Commission?s DG Information Society and Media (DG INFSO). Informed by a large dataset recording the details of funded projects, the simulation model is set up to reproduce and assess the funding strategies, the funded organisations and projects, and the resulting network structures of the Commission?s Framework 7 (FP7) programme. To address the evaluative questions of DG INFSO, this model, extrapolated into the future without any policy changes, is taken as an evidence-based benchmark for further experiments.
Against this baseline scenario the following example policy changes are tested: (i) What if there were changes to the thematic scope of the programme? (ii) What if there were changes to the instruments of funding? (iii) What if there were changes to the overall amount of programme funding? (iv) What if there were changes to increase Small and Medium Enterprise (SME) participation? The results of these simulation experiments reveal some likely scenarios as policy options for Horizon 2020. The paper thus demonstrates that realistic modelling with a close data-to-model link can directly provide policy advice.
GILBERT GN, DALE A, ARBER S (1983) THE GENERAL HOUSEHOLD SURVEY AS A SOURCE FOR SECONDARY ANALYSIS, SOCIOLOGY-THE JOURNAL OF THE BRITISH SOCIOLOGICAL ASSOCIATION 17 (2) pp. 255-259 BRITISH SOCIOLOGICAL ASSOC
Dresner S, Jackson T, Gilbert N (2006) History and social responses to environmental tax reform in the United Kingdom, ENERGY POLICY 34 (8) pp. 930-939 ELSEVIER SCI LTD
GILBERT GN (1977) COMPETITION, DIFFERENTIATION AND CAREERS IN SCIENCE, SOCIAL SCIENCE INFORMATION SUR LES SCIENCES SOCIALES 16 (1) pp. 103-123 SAGE PUBLICATIONS LTD
MULKAY M, GILBERT GN (1982) JOKING APART - SOME RECOMMENDATIONS CONCERNING THE ANALYSIS OF SCIENTIFIC CULTURE, SOCIAL STUDIES OF SCIENCE 12 (4) pp. 585-613 SAGE PUBLICATIONS LTD
Gilbert G, Troitzsch K (1997) Social science microsimulation, Bulletin Methodologie Sociologique (56) pp. 71-83
Gilbert N (2005) La simulazione basata su agenti:come affrontare la complessita' dei sistemi sociali, In: Albino V, Carbonara N, Giannoccaro I (eds.), Organizzazioni e Complessità. Muoversi tra ordine e caos per affrontare il cambiamento pp. 119-138 F. Angeli
Mulkay MJ, Gilbert GN (1983) Opening Pandora?s Box, Sociology of the Arts and Sciences 4 pp. 113-139
Matthews RB, Gilbert NG, Roach A, Polhill JG, Gotts NM (2007) Agent-based land-use models: A review of applications, Landscape Ecology 22 (10) pp. 1447-1459
Agent-based modelling is an approach that has been receiving attention by the land use modelling community in recent years, mainly because it offers a way of incorporating the influence of human decision-making on land use in a mechanistic, formal, and spatially explicit way, taking into account social interaction, adaptation, and decision-making at different levels. Specific advantages of agent-based models include their ability to model individual decision-making entities and their interactions, to incorporate social processes and non-monetary influences on decision-making, and to dynamically link social and environmental processes. A number of such models are now beginning to appear-it is timely, therefore, to review the uses to which agent-based land use models have been put so far, and to discuss some of the relevant lessons learnt, also drawing on those from other areas of simulation modelling, in relation to future applications. In this paper, we review applications of agent-based land use models under the headings of (a) policy analysis and planning, (b) participatory modelling, (c) explaining spatial patterns of land use or settlement, (d) testing social science concepts and (e) explaining land use functions. The greatest use of such models so far has been by the research community as tools for organising knowledge from empirical studies, and for exploring theoretical aspects of particular systems. However, there is a need to demonstrate that such models are able to solve problems in the real world better than traditional modelling approaches. It is concluded that in terms of decision support, agent-based land-use models are probably more useful as research tools to develop an underlying knowledge base which can then be developed together with end-users into simple rules-of-thumb, rather than as operational decision support tools. © 2007 Springer Science+Business Media B.V.
Gilbert N (2006) When does social simulation need cognitive models?, In: Sun R (eds.), Cognition and Multi-Agent Interaction: From Cognitive Modeling to Social Simulation pp. 428-432 Cambridge University Press
Gilbert G (1992) Researching Social Life, Sage
Gilbert N (1999) Computer Simulation in the Social Sciences, Sage
Gilbert N, Troitzsch KG (2005) Simulation for the social scientist, Open University Press
Salgado M, Gilbert N (2013) Emergence and Communication in Computational Sociology, Journal for the Theory of Social Behaviour 43 (1) pp. 87-110
Computational sociology models social phenomena using the concepts of emergence and downward causation. However, the theoretical status of these concepts is ambiguous; they suppose too much ontology and are invoked by two opposed sociological interpretations of social reality: the individualistic and the holistic. This paper aims to clarify those concepts and argue in favour of their heuristic value for social simulation. It does so by proposing a link between the concept of emergence and Luhmann's theory of communication. For Luhmann, society emerges from the bottom-up as communication and he describes the process by which society limits the possible selections of individuals as downward causation. It is argued that this theory is well positioned to overcome some epistemological drawbacks in computational sociology. © 2012 Blackwell Publishing Ltd.
LACZKO F, DALE A, ARBER SSS, GILBERT GN (1988) EARLY RETIREMENT IN A PERIOD OF HIGH UNEMPLOYMENT, JOURNAL OF SOCIAL POLICY 17 pp. 313-333 CAMBRIDGE UNIV PRESS
Gilbert GN, Arber S, Dale A (1981) Conversion of GHS into SPSS compatible files, 1973-1976, SSRC Survey Archive Bulletin (20) pp. 1-2
Gilbert N (1996) European Union Social Science Research: Chinks in the wall, European Sociologist (4) pp. 6-7
Ahrweiler P, Gilbert N, Pyka A (2011) Agency and structure: a social simulation of knowledge-intensive industries, Computational and Mathematical Organization Theory 17 (1) pp. 59-76 Springer
Modern knowledge-intensive economies are complex social systems
where intertwining factors are responsible for the shaping of emerging industries: the
self-organising interaction patterns and strategies of the individual actors (an agencyoriented
pattern) and the institutional frameworks of different innovation systems (a
structure-oriented pattern). In this paper, we examine the relative primacy of the two
patterns in the development of innovation networks, and find that both are important.
In order to investigate the relative significance of strategic decision making by innovation
network actors and the roles played by national institutional settings, we use
an agent-based model of knowledge-intensive innovation networks, SKIN.We experiment
with the simulation of different actor strategies and different access conditions
to capital in order to study the resulting effects on innovation performance and size
of the industry. Our analysis suggests that actors are able to compensate for structural
limitations through strategic collaborations. The implications for public policy are
outlined.
Arber S, Gilbert GN, Dale A, Rajan L (1985) Poverty and Income in Britain, Longmans Educational Publishing
Arber S, Dale A, Gilbert GN (1986) The limitations of existing social class classifications for women, In: Jacoby A (eds.), The measurement of social class pp. 73-93 Social Research Association
Sanfilippo A, Gilbert GN, Greaves M (2012) Technosocial predictive analytics for security
informatics,
Security Informatics 1 (1) 8 Springer
Gilbert GN (1990) Complex systems, ethnomethodology and interaction analysis, American Association for Artificial Intelligence
Pyka A, Gilbert N, Ahrweiler P (2007) Simulating knowledge-generation and distribution processes in innovation collaborations and networks, pp. 667-693 Taylor & Francis Inc
An agent-based simulation model representing a theory of the dynamic processes involved in innovation in modern knowledge-based industries is described. The agent-based approach allows the representation of heterogenous agents that have individual and varying stocks of knowledge. The simulation is able to model uncertainty, historical change, effect of failure on the agent population, and agent learning from experience, from individual research and from partners and collaborators. The aim of the simulation exercises is to show that the artificial innovation networks show certain characteristics they share with innovation networks in knowledge intensive industries and which are difficult to be integrated in traditional models of industrial economics.
Fordham A, Gilbert N (1995) On the nature of rules and conversation, AI and Society 9 (4) pp. 356-372
Jiang J, Pozza R, Gunnarsdottir K, Gilbert GN, Moessner K (2017) Recognising Activities at Home: Digital and Human Sensors, Proceedings of ICFNDS ?17, Cambridge, United Kingdom, July 19-20, 2017 ACM, the Association for Computing Machinery
What activities take place at home? When do they occur, for how
long do they last and who is involved? Asking such questions is
important in social research on households, e.g., to study energyrelated
practices, assisted living arrangements and various aspects
of family and home life. Common ways of seeking the answers
rest on self-reporting which is provoked by researchers (interviews,
questionnaires, surveys) or non-provoked (time use diaries). Longitudinal
observations are also common, but all of these methods
are expensive and time-consuming for both the participants and
the researchers. The advances of digital sensors may provide an
alternative. For example, temperature, humidity and light sensors
report on the physical environment where activities occur, while
energy monitors report information on the electrical devices that
are used to assist the activities. Using sensor-generated data for
the purposes of activity recognition is potentially a very powerful
means to study activities at home. However, how can we quantify
the agreement between what we detect in sensor-generated
data and what we know from self-reported data, especially nonprovoked
data? To give a partial answer, we conduct a trial in a
household in which we collect data from a suite of sensors, as well
as from a time use diary completed by one of the two occupants.
For activity recognition using sensor-generated data, we investigate
the application of mean shift clustering and change points
detection for constructing features that are used to train a Hidden
Markov Model. Furthermore, we propose a method for agreement
evaluation between the activities detected in the sensor data and
that reported by the participants based on the Levenshtein distance.
Finally, we analyse the use of different features for recognising
different types of activities.
Barbrook-Johnson P, Badham J, Gilbert G (2016) Uses of agent-based modeling for health communication: The TELL ME case study, Health Communication 32 (8) pp. 939-944 Taylor & Francis
Government communication is an important management tool during a public health crisis, but understanding its impact is difficult. Strategies may be adjusted in reaction to developments on the ground and it is challenging to evaluate the impact of communication separately from other crisis management activities. Agent-based modeling is a well-established research tool in social science to respond to similar challenges. However, there have been few such models in public health. We use the example of the TELL ME agent-based model to consider ways in which a non-predictive policy model can assist policy makers. This model concerns individuals? protective behaviors in response to an epidemic, and the communication that influences such behavior. Drawing on findings from stakeholder workshops and the results of the model itself, we suggest such a model can be useful: (i) as a teaching tool, (ii) to test theory, and (iii) to inform data collection. We also plot a path for development of similar models that could assist with communication planning for epidemics.
Casnici N, Grimaldo F, Dondio P, Gilbert G, Squazzoni F (2017) Assessing peer review by gauging the fate of rejected manuscripts. The case of the Journal of Artificial Societies and Social Simulation, Scientometrics: an international journal for all quantitative aspects of the science of science, communication in science and science policy 113 (1) pp. 533-546 Springer Verlag
This paper investigates the fate of manuscripts that were rejected from JASSS-The Journal of Artificial Societies and Social Simulation, the flagship journal of social simulation. We tracked 456 manuscripts that were rejected from 1997 to 2011 and traced their subsequent publication as journal articles, conference papers or working papers. We compared the impact factor of the publishing journal and the citations of those manuscripts that were eventually published against the yearly impact factor of JASSS and the number of citations achieved by the JASSS mean and top cited articles. Only 10% of the rejected manuscripts were eventually published in a journal that was indexed in the Web of Science (WoS), although most of the rejected manuscripts were published elsewhere. Being exposed to more than one round of reviews before rejection, having received a more detailed reviewer report and being subjected to higher inter-reviewer disagreement were all associated with the number of citations received when the manuscript was eventually published. This indicates that peer review could contribute to increasing the quality even of rejected manuscripts.
Gilbert G, Ahrweiler P, Pyka A (2007) Learning in innovation networks: Some simulation experiments, Physica A: Statistical Mechanics and its Applications 378 (1) pp. 100-109
According to the organizational learning literature, the greatest competitive advantage a firm has is its ability to learn. In this paper, a framework for modeling learning competence in firms is presented to improve the understanding of managing innovation. Firms with different knowledge stocks attempt to improve their economic performance by engaging in radical or incremental innovation activities and through partnerships and networking with other firms. In trying to vary and/or to stabilize their knowledge stocks by organizational learning, they attempt to adapt to environmental requirements while the market strongly selects on the results. The simulation experiments show the impact of different learning activities, underlining the importance of innovation and learning. (c) 2006 Elsevier B.V. All rights reserved.
Hamill L, Gilbert GN (2009) Social circles: a simple structure for agent-based social network models, Journal of Artificial Societies and Social Simulation 12 (2) SimSoc Consortium
None of the standard network models fit well with sociological observations of real social
networks. This paper presents a simple structure for use in agent-based models of large
social networks. Taking the idea of social circles, it incorporates key aspects of large social
networks such as low density, high clustering and assortativity of degree of connectivity. The
model is very flexible and can be used to create a wide variety of artificial social worlds.
Brunton-Smith I, Carpenter J, Kenward M, Tarling R (2014) Multiple Imputation for handling missing data in social research, Social Research Update (65) Department of Sociology, University of Surrey

Missing data frequently occurs in
quantitative social research. For
example, in a survey of individuals,
some of those selected for interview
will not agree to participate (unit
non-response) and others who do
agree to be interviewed will not
always answer all the questions (item
non-response).

At its most benign, missing data
reduces the achieved sample size,
and consequently the precision of
estimates. However, missing data
can also result in biased inferences
about outcomes and relationships
of interest. Broadly, if the underlying,
unseen, responses from those
individuals in the survey frame who
have one or more missing responses
differ systematically from those
individuals in the survey frame whose
responses are all observed, then any
analysis restricted to the subset of
individuals whose responses are all
observed runs the risk of producing
biased inferences for the target population.

Thus every researcher needs to take
seriously the potential consequences
of missing data. This paper describes
the use of Multiple Imputation (MI)
to correct estimates for missing
data, under a general assumption
about the cause, or reason for
missing data. This is generally termed
the missingness mechanism. MI
has robust theoretical properties
while being flexible, generalisable
and readily available in a range of
statistical software.

Jiang J, Pozza R, Gunnarsdottir K, Gilbert G, Moessner K (2017) Using Sensors to Study Home Activities, Journal of Sensor and Actuator Networks 6 (4) MDPI
Understanding home activities is important in social research to study aspects of home life, e.g., energy-related practices and assisted living arrangements. Common approaches to identifying which activities are being carried out in the home rely on self-reporting, either retrospectively (e.g., interviews, questionnaires, and surveys) or at the time of the activity (e.g., time use diaries). The use of digital sensors may provide an alternative means of observing activities in the home. For example, temperature, humidity and light sensors can report on the physical environment where activities occur, while energy monitors can report information on the electrical devices that are used to assist the activities. One may then be able to infer from the sensor data which activities are taking place. However, it is first necessary to calibrate the sensor data by matching it to activities identified from self-reports. The calibration involves identifying the features in the sensor data that correlate best with the self-reported activities. This in turn requires a good measure of the agreement between the activities detected from sensor-generated data and those recorded in self-reported data. To illustrate how this can be done, we conducted a trial in three single-occupancy households from which we collected data from a suite of sensors and from time use diaries completed by the occupants. For sensor-based activity recognition, we demonstrate the application of Hidden Markov Models with features extracted from mean-shift clustering and change points analysis. A correlation-based feature selection is also applied to reduce the computational cost. A method based on Levenshtein distance for measuring the agreement between the activities detected in the sensor data and that reported by the participants is demonstrated. We then discuss how the features derived from sensor data can be used in activity recognition and how they relate to activities recorded in time use diaries.
Commons-Based Peer Production (CBPP) is a new model of socio-economic production in which groups of individuals cooperate with each other without a traditional hierarchical organisation to produce common and public goods, such as Wikipedia or GNU/Linux. There is a need to understand how these communities govern and organise themselves as they grow in size and complexity. Following an ethnographic approach, this thesis explores the emergence of and changes in the organisational structures and processes of Drupal: a large and global CBBP community which, over the past fifteen years, has coordinated the work of hundreds of thousands of participants to develop a technology which currently powers more than 2% of websites worldwide.

Firstly, this thesis questions and studies the notion of contribution in CBPP communities, arguing that contribution should be understood as a set of meanings which are under constant negotiation between the participants according to their own internal logics of value. Following a constructivist approach, it shows the relevance played by less visible contribution activities such as the organisation of events.

Secondly, this thesis explores the emergence and inner workings of the socio-technical systems which surround contributions related to the development of projects and the organisation of events. Two intertwined organisational dynamics were identified: formalisation in the organisational processes and decentralisation in decision-making.

Finally, this thesis brings together the empirical data from this exploration of socio-technical systems with previous literature on self-organisation and organisation studies, to offer an account of how the organisational changes resulted in the emergence of a polycentric model of governance, in which different forms of organisation varying in their degree of organicity co-exist and influence each other.

Gilbert G, Ahrweiler P, Barbrook-Johnson P, Narasimhan K, Wilkinson H (2018) Computational Modelling of Public Policy:
Reflections on Practice,
Journal of Artificial Societies and Social Simulation 21 (1) pp. 1-14 SimSoc Consortium
Computational models are increasingly being used to assist in developing, implementing and evaluating
public policy. This paper reports on the experience of the authors in designing and using computational
models of public policy (?policy models?, for short). The paper considers the role of computational models in
policy making, and some of the challenges that need to be overcome if policy models are to make an effective
contribution. It suggests that policy models can have an important place in the policy process because
they could allow policy makers to experiment in a virtual world, and have many advantages compared with
randomised control trials and policy pilots. The paper then summarises some general lessons that can be extracted
from the authors? experience with policy modelling. These general lessons include the observation that
often the main benefit of designing and using a model is that it provides an understanding of the policy domain,
rather than the numbers it generates; that care needs to be taken that models are designed at an appropriate
level of abstraction; that although appropriate data for calibration and validation may sometimes be in short
supply, modelling is often still valuable; that modelling collaboratively and involving a range of stakeholders
from the outset increases the likelihood that the model will be used and will be fit for purpose; that attention
needs to be paid to effective communication between modellers and stakeholders; and that modelling for public
policy involves ethical issues that need careful consideration. The paper concludes that policy modelling
will continue to grow in importance as a component of public policy making processes, but if its potential is to
be fully realised, there will need to be a melding of the cultures of computational modelling and policy making.
Agent-based simulation can model simple micro-level mechanisms capable of generating macro-level patterns, such as frequency distributions and network structures found in bibliometric data. Agent-based simulations of organisational learning have provided analogies for collective problem solving by boundedly rational agents employing heuristics. This paper brings these two areas together in one model of knowledge seeking through scientific publication. It describes a computer simulation in which academic papers are generated with authors, references, contents, and an extrinsic value, and must pass through peer review to become published. We demonstrate that the model can fit bibliometric data for a token journal, Research Policy. Different practices for generating authors and references produce different distributions of papers per author and citations per paper, including the scale-free distributions typical of cumulative advantage processes. We also demonstrate the model?s ability to simulate collective learning or problem solving, for which we use Kauffman?s NK fitness landscape. The model provides evidence that those practices leading to cumulative advantage in citations, that is, papers with many citations becoming even more cited, do not improve scientists? ability to find good solutions to scientific problems, compared to those practices that ignore past citations. By contrast, what does make a difference is referring only to publications that have successfully passed peer review. Citation practice is one of many issues that a simulation model of science can address when the data-rich literature on scientometrics is connected to the analogy-rich literature on organisations and heuristic search.
Skeldon A, Schiller F, Yang A, Balke-Visser T, Penn A, Gilbert G (2018) Agent-based modelling to predict policy outcomes: a food waste recycling example, Environmental Science and Policy 87 pp. 85-91 Elsevier

Optimising policy choices to steer social/economic systems efficiently
towards desirable outcomes is challenging. The inter-dependent nature of
many elements of society and the economy means that policies designed to
promote one particular aspect often have secondary, unintended, effects.
In order to make rational decisions, methodologies and tools to assist
the development of intuition in this complex world are needed. One
approach is the use of agent-based models. These have the ability to
capture essential features and interactions and predict outcomes in a way
that is not readily achievable through either equations or words alone.

In this paper we illustrate how agent-based models can be used in
a policy setting by using an example drawn from the biowaste industry.
This example describes the growth of in-vessel composting and anaerobic
digestion to reduce food waste going to landfill in response to policies in
the form of taxes and financial incentives. The fundamentally dynamic
nature of an agent-based modelling approach is used to demonstrate that policy outcomes depend not just on current policy levels but also on the
historical path taken.

Hodkinson P (2008) Grounded Theory and Inductive Research, In: Gilbert G (eds.), Researching Social Life (5) pp. 80-100 Sage Publications Ltd
This chapter focuses upon the principles and procedures associated with grounded theory, which has become the most well known approach to inductive social research. Having distinguished between inductive and deductive approaches to the development of theory through research in a general sense, the chapter goes on to outline the key features of grounded theory, including the notions of theoretical sampling, coding, constant comparison, and theoretical saturation. The focus here is partly on providing practical information and examples on how to carry out grounded theory research but also on understanding the justifications and arguments offered by proponents for adopting this approach. Having set out such procedures and arguments, we will examine some of the criticisms which have been levelled against grounded theory. It is suggested that, although highly influential, grounded theory is not very often followed to the letter and that ? for better or worse ? it is more common for researchers to adopt one or more elements associated with approach as part of their efforts to develop theory through research.
Calder M, Craig C, Culley D, de Cani R, Donnelly C, Douglas R, Edmonds B, Gascoigne J, Gilbert G, Hargrove C, Hinds D, Lane D, Mitchell D, Pavey G, Robertson D, Rosewell B, Sherwin S, Walport M, Wilson A (2018) Computational modelling for decision-making: where, why, what, who and how, Royal Society Open Science 5 (6) The Royal Society
In order to deal with an increasingly complex world, we need ever more sophisticated computational models that can help us make decisions wisely and understand the potential consequences of choices. But creating a model requires far more than just raw data and technical skills: it requires a close collaboration between model commissioners, developers, users and reviewers. Good modelling requires its users and commissioners to understand more about the whole process, including the different kinds of purpose a model can have and the different technical bases. This paper offers a guide to the process of commissioning, developing and deploying models across a wide range of domains from public policy to science and engineering. It provides two checklists to help potential modellers, commissioners and users ensure they have considered the most significant factors that will determine success. We conclude there is a need to reinforce modelling as a discipline, so that misconstruction is less likely; to increase understanding of modelling in all domains, so that the misuse of models is reduced; and to bring commissioners closer to modelling, so that the results are more useful.
Badham Jennifer, Chattoe-Brown Edmund, Gilbert Nigel, Chalabi Zaid, Kee Frank, Hunter Ruth F (2018) Developing Agent-Based Models of Complex Health
Behaviour,
Health and Place Elsevier
Managing non-communicable diseases requires policy makers to adopt a whole
systems perspective that adequately represents the complex causal architecture
of human behaviour. Agent-based modelling is a computational method to un-
derstand the behaviour of complex systems by simulating the actions of entities
within the system, including the way these individuals in
uence and are in
u-
enced by their physical and social environment. The potential benefits of this
method have led to several calls for greater use in public health research. We
discuss three challenges facing potential modellers: model specification, obtain-
ing required data, and developing good practices. We also present steps to assist
researchers to meet these challenges and implement their agent-based model.