Alex Penn

Dr Alex Penn

Research Fellow
+44 (0)1483 682788
26 AD 03


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My publications


Penn AS, Knight CJK, Lloyd DJB, Avitabile D, Kok K, Schiller F, Woodward A, Druckman A, Basson L (2013) Participatory Development and Analysis of a Fuzzy Cognitive Map of the Establishment of a Bio-Based Economy in the Humber Region, PLOS ONE 8 (11) ARTN e78319 PUBLIC LIBRARY SCIENCE
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
Powers ST, Penn AS, Watson RA (2008) The efficacy of group selection is increased by coexistence dynamics within groups, Artificial Life XI: Proceedings of the 11th International Conference on the Simulation and Synthesis of Living Systems, ALIFE 2008 pp. 498-505
Selection on the level of loosely associated groups has been suggested as a route towards the evolution of cooperation between individuals and the subsequent formation of higherlevel biological entities. Such group selection explanations remain problematic, however, due to the narrow range of parameters under which they can overturn within-group selection that favours selfish behaviour. In principle, individual selection could act on such parameters so as to strengthen the force of between-group selection and hence increase cooperation and individual fitness, as illustrated in our previous work. However, such a process cannot operate in parameter regions where group selection effects are totally absent, since there would be no selective gradient to follow. One key parameter, which when increased often rapidly causes group selection effects to tend to zero, is initial group size, for when groups are formed randomly then even moderately sized groups lack significant variance in their composition. However, the consequent restriction of any group selection effect to small sized groups is derived from models that assume selfish types will competitively exclude their more cooperative counterparts at within-group equilibrium. In such cases, diversity in the migrant pool can tend to zero and accordingly variance in group composition cannot be generated. In contrast, we show that if within-group dynamics lead to a stable coexistence of selfish and cooperative types, then the range of group sizes showing some effect of group selection is much larger. © 2007
Understanding and manipulating bacterial biofilms is crucial in medicine, ecology and agriculture and has potential applications in bioproduction, bioremediation and bioenergy. Biofilms often resist standard therapies and the need to develop new means of intervention provides an opportunity to fundamentally rethink our strategies. Conventional approaches to working with biological systems are, for the most part, ?brute force?, attempting to effect control in an input and effort intensive manner and are often insufficient when dealing with the inherent non-linearity and complexity of living systems. Biological systems, by their very nature, are dynamic, adaptive and resilient and require management tools that interact with dynamic processes rather than inert artefacts. I present an overview of a novel engineering philosophy which aims to exploit rather than fight those properties, and hence provide a more efficient and robust alternative. Based on a combination of evolutionary theory and whole-systems design, its essence is what I will call systems aikido; the basic principle of aikido being to interact with the momentum of an attacker and redirect it with minimal energy expenditure, using the opponent?s energy rather than one?s own. In more conventional terms, this translates to a philosophy of equilibrium engineering, manipulating systems? own self-organisation and evolution so that the evolutionarily or dynamically stable state corresponds to a function which we require. I illustrate these ideas with a description of a proposed manipulation of environmental conditions to alter the stability of co-operation in the context of Pseudomonas aeruginosa biofilm infection of the cystic fibrosis lung.
Schiller F, Penn A, Druckman A, Basson L, Royston K (2014) Exploring Space, Exploiting Opportunities The Case for Analyzing Space in Industrial Ecology, JOURNAL OF INDUSTRIAL ECOLOGY 18 (6) pp. 792-798 WILEY-BLACKWELL
Schiller F, Penn AS, Basson L (2014) Analyzing networks in industrial ecology - a review of Social-Material Network Analyses, Journal of Cleaner Production 76 (1) pp. 1-11
This review concerns the methodological challenges that industrial ecology faces in integrating natural and social sciences. Network analysis can be seen as the most promising method to mediate between industrial ecology's overall systems approach and the complex structures found in society. It is a well established method across scientific disciplines, including the social sciences. It has been successfully applied in industrial ecology, in which localized phenomena of industrial symbiosis have been a key focus, and where metrics from both the social and natural sciences are used to understand socio-metabolic structures. In this paper we classify such studies as Social-Material Network Analyses and we discuss the body of work, drawing on network analyses from various disciplines. A challenge is the hierarchical nature of industrial networks and how it can be addressed socially. We discuss the opportunities and limitations of metric-driven network analysis and offer a review of methodological options for Social-Material Network Analyses. © 2014 The Authors.
Knight CJK, Lloyd DJB, Penn AS (2014) Linear and sigmoidal fuzzy cognitive maps: An analysis of fixed points, Applied Soft Computing Journal 15 pp. 193-202
Fuzzy cognitive mapping is commonly used as a participatory modelling technique whereby stakeholders create a semi-quantitative model of a system of interest. This model is often turned into an iterative map, which should (ideally) have a unique stable fixed point. Several methods of doing this have been used in the literature but little attention has been paid to differences in output such different approaches produce, or whether there is indeed a unique stable fixed point. In this paper, we seek to highlight and address some of these issues. In particular we state conditions under which the ordering of the variables at stable fixed points of the linear fuzzy cognitive map (iterated to) is unique. Also, we state a condition (and an explicit bound on a parameter) under which a sigmoidal fuzzy cognitive map is guaranteed to have a unique fixed point, which is stable. These generic results suggest ways to refine the methodology of fuzzy cognitive mapping. We highlight how they were used in an ongoing case study of the shift towards a bio-based economy in the Humber region of the UK. © 2013 Elsevier B.V. All rights reserved.
Penn AS, Jensen PD, Basson L, Druckman A, Woodward A, Schiller F (2014) Sketching a network portrait of the humber region, Complexity 19 (6) pp. 54-72
Industrial systems can be represented as networks of organizations connected by flows of materials, energy, and money. This network context may produce unexpected consequences in response to policy intervention, so improved understanding is vital; however, industrial network data are commonly unavailable publically. Using a case study in the Humber region, UK, we present a novel methodology of "network coding" of semistructured interviews with key industrial and political stakeholders, in combination with an "industrial taxonomy" of network archetypes developed to construct an approximation of the region's networks when data are incomplete. This article describes our methodology and presents the resulting network. © 2014 Wiley Periodicals, Inc.
Penn AS, Watson RA, Penn AS, Conibear TC, Kraaijeveld AR, Webb JS, Conibear TC (2012) Can Simpson's paradox explain co-operation in Pseudomonas aeruginosa biofilms?, FEMS Immunology and Medical Microbiology
Co-operative behaviours, such as the production of public goods, are commonly displayed by bacteria in biofilms and can enhance their ability to survive in environmental or clinical settings. Non-co-operative cheats commonly arise and should, theoretically, disrupt co-operative behaviour. Its stability therefore requires explanation, but no mechanisms to suppress cheating within biofilms have yet been demonstrated experimentally. Theoretically, repeated aggregation into groups, interleaved with dispersal and remixing, can increase co-operation via a 'Simpson's paradox'. That is, an increase in the global proportion of co-operators despite a decrease in within-group proportions, via differential growth of groups. We investigate the hypothesis that microcolony formation and dispersal produces a Simpson's paradox that explains bacterial co-operation in biofilms. Using the production of siderophores in Pseudomonas aeruginosa as our model system for co-operation, we use well-documented co-operator and siderophore-deficient cheat strains to measure the frequency of co-operating and cheating individuals, in-situ within-microcolony structures. We detected significant within-type negative density-dependant effects that vary over microcolony development. However, we find no evidence of Simpson's paradox. Instead, we see clear within-microcolony spatial structure (cheats occupying the interior portions of microcolonies) that may violate the assumption required for Simpson's paradox that group members share equally in the public good. © 2012 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.
Moschoyiannis S, Elia N, Penn A, Lloyd D, Knight C (2016) A web-based tool for identifying strategic intervention points in complex systems, CASSTING 2016
Steering a complex system towards a desired outcome is a challenging task. The lack of clarity on the system?s exact architecture and the often scarce scientific data upon which to base the op- erationalisation of the dynamic rules that underpin the interactions between participant entities are two contributing factors. We describe an analytical approach that builds on Fuzzy Cognitive Map- ping (FCM) to address the latter and represent the system as a complex network. We apply results from network controllability to address the former and determine minimal control configurations - subsets of factors, or system levers, which comprise points for strategic intervention in steering the system. We have implemented the combination of these techniques in an analytical tool that runs in the browser, and generates all minimal control configurations of a complex network. We demonstrate our approach by reporting on our experience of working alongside industrial, local-government, and NGO stakeholders in the Humber region, UK. Our results are applied to the decision-making process involved in the transition of the region to a bio-based economy.
Powers ST, Penn AS, Watson RA (2007) Individual selection for cooperative group formation, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4648 LNAI pp. 585-594
It is well known that certain environmental conditions, such as a spatially structured population, can promote the evolution of cooperative traits. However, such conditions are usually assumed to be externally imposed. In this paper, we present a model that allows the conditions that promote or hinder cooperation to arise adaptively via individual selection. Consequently, instead of selection simply favouring cooperation under imposed environmental conditions, in our model selection also operates on the conditions themselves via a niche construction process. Results are presented that show that the conditions that favour cooperation can evolve, even though those that favour selfish behaviour are also available and are initially selected for. © Springer-Verlag Berlin Heidelberg 2007.
Penn A, knight C, Chalkias G, Velenturf A, Lloyd D (2016) Extending Participatory Fuzzy Cognitive Mapping with a Control Nodes Methodology: a case study of the development bio-based economy in the Humber region, UK, In: Gray S, Paolisso M, Jordan R, Gray S (eds.), Environmental Modeling with Stakeholders Springer International Publishing
Fuzzy Cognitive Mapping (FCM) is a widely used participatory modeling methodology in which stakeholders collaboratively develop a cognitive map (a weighted, directed graph), representing the perceived causal structure of their sys- tem. FCM can be an extremely useful tool to enable stakeholders to collaborative- ly represent and consolidate their understanding of the structure of their system. Analysis of an FCM using tools from network theory enables the calculation of ?control configurations? for the system; subsets of system factors which if con- trolled could be used to drive the system to any given state. We have developed a technique that allows us to calculate all possible, minimally-sized control configu- rations of a stakeholder-generated FCM within a workshop context. In order to evaluate our results in terms of real world ?controllability,? stakeholders score all
factors on the basis of their ability to influence them, allowing us to rank the con- figurations by their potential local controllability. This provides a starting point for discussions about effective policy, or other interventions from the specific perspective of regional actors and decision makers. We describe this methodology and report on a participatory process in which it was tested: the construction of an FCM focusing on the development of a bio-based economy in the Humber region (UK) by key stakeholders from local companies and organizations. Results and stakeholder responses are discussed in the context of our case study, but also, more generally, in the context of the use of participatory modeling for decision making in complex socio-ecological-economic systems.
Knight CJK, Penn AS, Hoyle RB (2014) Comparing the effects of mutualism and competition on industrial districts, Physica A: Statistical Mechanics and its Applications 416 pp. 541-557
© 2014 Elsevier B.V. All rights reserved.Industrial districts are made up of numerous firms or industries interacting in myriad ways. We create and study a model of trade and service interactions in an industrial district, and then extend it to investigate the effect of both positive (mutualistic) and negative (competitive) non-trade interactions on the behaviour of two different types of industrial district - Marshallian and hub-and-spoke. In particular we study whether the structure of the district, or the positioning of the relationships, makes a difference to the outcome for the district as a whole. We find that both these aspects make a difference. For instance, in both Marshallian and hub-and-spoke districts a competitive relationship between firms that are directly linked by trade has a stronger effect than competition between firms that are not. On the other hand in a Marshallian district it is possible to make the district more 'egalitarian' by adding a mutualistic relationship between suppliers or between intermediary firms, but this effect is not seen in hub-and-spoke districts. We highlight for further investigation a hypothesis suggested by our results that the effects of mutualism on an industrial district are more pronounced than those of competition.
Powers ST, Penn AS, Watson RA (2011) "The concurrent evolution of cooperation and the population structures that support it." 65.6 (2011): 1527-1543., Evolution 65 (6) pp. 1527-1543