Dr Kavin Narasimhan


Research Fellow
B.E. (Computer Science and Engineering), PhD (Computer Science), FHEA

Academic and research departments

Department of Sociology.

Biography

Areas of specialism

Human Behaviour Modelling; Energy Modelling; Socio-ecological Systems (SES) Modelling ; Agent-based Modelling; Java; Teaching in Higher Education

My qualifications

2021
Fellow of The Higher Education Academy (FHEA)
Higher Education Academy
2016
PhD Computer Science (Passed with No Corrections)
Queen Mary University of London, UK
2009
Sun Certified Java Professional (SCJP)
Sun Microsystems
2008
B.E. Computer Science and Engineering
Anna University, India

My publications

Publications

Kavin Narasimhan, Nigel Gilbert, Corinna Elsenbroich (2022)WATERING Crop Growth Reusable Building Block, In: WATERING Irrigation Reusable Building Block Zenodo

This asset is available at Zenodo: https://doi.org/10.5281/zenodo.6323653 This NetLogo model is a reusable component (also referred to as a Reusable Building Block or RBB) called WATERING_CROPGROWTH_RBB. Please: Download the WATERING_CROPGROWTH_RBB.nlogo file Open downloaded file Click on the Info. tab for model description, context specification, executable demonstration, and suggestions to extend/adapt/use the model WATERING_CROPGROWTH_RBB is a sub-model of the WATER user associations at the Interface of Nexus Governance (WATERING) model (for further information about WATERING, please see https://www.youtube.com/watch?v=U-nqs9ak2nY) Please email Dr Kavin Narasimhan (k.narasimhan@surrey.ac.uk) for comments or questions. If you adapt/use the WATERING_CROPGROWTH_RBB model, we would appreciate if you cite our repo, as well as the Watershed model (http://ccl.northwestern.edu/netlogo/models/community/watershed) licensed under the Creative Commons Attribution-NonCommercial-ShareAlike License based on which we have created the irrigation component of WATERING_CROPGROWTH_RBB. Note: WATERING was developed as an exploratory tool to understand and explain how participatory irrigation management through Water User Associations (WUAs) work. The model allows exploring the impact of community-based water management (through WUAs) on water availability, water use and economic productivity within an irrigation scheme. While WATERING_CROPGROWTH_RBB is not WATERING, it is a sub-model of WATERING to simulate water flow and crop growth within an irrigation scheme - you can change the values of the input controls via the Interface and see how that affects water use and crop growth within the scheme (through visualisation in the NetLogo world and output plots). Our complete WATERING model includes other components to simulate various aspects of community-based water management through WUAs. Please get in touch with the author if you are interested in the complete WATERING model.

Kavin Narasimhan, Nigel Gilbert, Corinna Elsenbroich (2022)WATERING Irrigation Reusable Building Block, In: WATERING Crop Growth Reusable Building Block

This asset is available at Zenodo: https://doi.org/10.5281/zenodo.6323633 This NetLogo model is a reusable component (also referred to as a Reusable Building Block or RBB) called WATERING_IRRIGATION_RBB. Please: Download the WATERING_IRRIGATION_RBB.nlogo file Open downloaded file Click on the Info. tab for model description, context specification, executable demonstration, and suggestions to extend/adapt/use the model WATERING_IRRIGATION_RBB is a sub-model of the WATER user associations at the Interface of Nexus Governance (WATERING) model (for further information about WATERING, please see https://www.youtube.com/watch?v=U-nqs9ak2nY) Please email Dr Kavin Narasimhan (k.narasimhan@surrey.ac.uk) for comments or questions. If you adapt/use the WATERING_IRRIGATION_RBB model, we would appreciate if you cite our repo, as well as the Watershed model (http://ccl.northwestern.edu/netlogo/models/community/watershed) licensed under the Creative Commons Attribution-NonCommercial-ShareAlike License based on which we have created this model. Please see the Info tab of the model for further documentation.

Kavin Narasimhan, GEOFFREY NIGEL GILBERT, Aimie Hope, THOMAS MARK ROBERTS Demystifying Energy Demand using a Practice-centric Agent-based Model University of Surrey

The rational choice framework is commonly used in many energy demand models and energy economic policy models. However, the notion of reasoned decision-making underpinning the rational actor models is less useful to explain the dynamics of routine household activities (e.g., cooking, showering, heating, etc.) which result in energy use. An alternative body of work collectively referred to as social practice theories offers a more practical explanation of routines. It is also argued that practices, i.e. the routine activities that people do in the service of normal everyday living, is at the centre of social change, and hence should be the focus of interventions concerned with demand reduction. One of the main criticisms of social practice theories, however, is that the concepts proposed are high-level and abstract and hence difficult to apply to real-world problems. Most existing practice-centric models are also abstract implementations. To address this gap, in this paper, we present a concrete, empirically-based practice-centric agent-based model to simulate the dynamics of household heating practices. We also use the model to explore consumer response to a simulated price-based demand response scheme. We show how a practice-centric approach leads to a more realistic understanding of the energy use patterns of households by revealing the underlying contexts of consumption. The overall motivation is that by gaining insight into the trajectories of unsustainable energy consuming practices, it might be possible to propose alternative pathways that allow more sustainable practices to take hold.

Kavin Narasimhan, GEOFFREY NIGEL GILBERT, CORINNA JULIA ELSENBROICH A Computational Model to Explore Decentralised Water Governance University of Surrey

https://blogs.surrey.ac.uk/sociology/2020/02/18/a-computational-model-to-explore-decentralised-water-governance/

Kavin Narasimhan, GEOFFREY NIGEL GILBERT, CORINNA JULIA ELSENBROICH Community based water governance University of Surrey

https://www.youtube.com/watch?v=U-nqs9ak2nY

Kavin Narasimhan, THOMAS MARK ROBERTS, MARIA XENITIDOU, GEOFFREY NIGEL GILBERT Using ABM to Clarify and Refine Social Practice Theory

We use an agent-based model to help to refine and clarify social practice theory, wherein the focus is neither on individuals nor on any form of societal totality, but on the repeated performances of practices ordered across space and time. The recursive relationship between social practices and practitioners (individuals performing practices) is strongly emphasised in social practice theory. We intend to have this recursive relationship unfold dynamically in a model where practitioners and social practices are both considered as agents. Model conceptualisation is based on the principle of structuration theory—the focus is neither on micro causing macro nor on macro influencing micro, but on the duality between structure (macro) and agency (micro). In our case, we conceptualise the duality between practitioners and practices based on theoretical insights from social practices literature; where information is unclear or insufficient, we make systematic assumptions and account for these.

Kavin Narasimhan, GEOFFREY NIGEL GILBERT, CORINNA JULIA ELSENBROICH An Integrated Model to Assess the Impacts of Dams in Transboundary River Basins

This extended abstract presents an integrated agent-based and hydrological model to explore the impacts of dams in transboundary river basins where riparian nations have competing water uses. The purpose of the model is to explore the effects of interactions between stakeholders from multiple levels and sectors on the management of dams and its subsequent effects on the water-energy-food-environment (WEFE) nexus in river basins.

Nigel Gilbert, P Ahrweiler, Peter Barbrook-Johnson, Kavin Narasimhan, H Wilkinson (2018)Computational Modelling of Public Policy: Reflections on Practice, In: Journal of Artificial Societies and Social Simulation21(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.

KP Narasimhan (2012)SPAGE: An Action Generation Engine to Support Spatial Patterns of Interaction in Multi-agent Simulations., In: S Omatu, JFDP Santana, S Rodríguez-González, JM Molina, AM Bernardos, JMC Rodríguez (eds.), DCAI151pp. 273-280
KP Narasimhan, G White (2014)Look, Who's Talking: Simulations of Agent Clusters., In: Y Demazeau, F Zambonelli, JM Corchado, J Bajo (eds.), PAAMS8473pp. 375-378 Springer
KP Narasimhan, G White (2014)Agent Clusters: The Usual vs. The Unusual., In: Y Demazeau, F Zambonelli, JM Corchado, J Bajo (eds.), PAAMS8473pp. 244-255 Springer
KP Narasimhan, G White (2013)An Agent-Based Analyses of F-formations., In: Y Demazeau, T Ishida, JM Corchado, J Bajo (eds.), PAAMS7879pp. 239-250
KP Narasimhan (2011)Towards modelling spatial cognition for intelligent agents., In: A Dittmar, P Forbrig (eds.), ECCEpp. 253-254

Additional publications