Gary Polhill

Research

My current research is focused on large-scale modelling to support policy scenario analysis, and getting the agent-based modelling community in a position where it more routinely takes advantage of high-performance computing, leading to us being able to deploy exascale applications of agent-based models to support real-time decision-making.

You can read more about the challenges faced by agent-based modellers accessing high-performance computing facilities, my motivation for growing the application of agent-based simulations in real-time decision-making context, and some strategic directions for agent-based modelling work that informs my current research.

Past research

I have been involved in a number of international and inter- and transdisciplinary research projects, listed below (note that for older projects links are liable to get mothballed):

• The CAVES (Complexity, Agents, Volatility, Evidence and Scale) project (2005-2008) was funded by the European Commission’s Sixth Framework Programme New and Emerging Science and Technology Pathfinder Initiative on Tackling Complexity in Science.
• PolicyGrid (2006-2009) and PolicyGrid II (2009-2012) were collaborations with the University of Aberdeen funded by the Economic and Social Research Council through the National Centre for e-Social Science. This work also led to a short project called SwarmCloud with the aim of grid-enabling the FEARLUS model. (See also PolicyGrid and PolicyGrid II entry on ESRC’s research catalogue.)
• The GILDED (Governance, Infrastructure, Lifestyle Dynamics and Energy Demand) project (2008-2012) was funded by the European Commission’s Seventh Framework Programme.
• The LOCAW (Low Carbon at Work: Modelling Agents and Organisations to Achieve Transition to a Low Carbon Europe) project (2011-2013) was funded by the European Commission’s Seventh Framework Programme.
• The MIRACLE (Mining Relationships Among Variables in Large Datasets from Complex Systems) project (2014-2015) was funded by Round 3 of the Digging into Data Challenge. The UK contribution was funded by the Economic and Social Research Council via Jisc.
• The GLAMURS (Green Lifestyles, Alternative Models and Up-scaling Regional Sustainability) project (2014-2016) was funded by the European Commission’s Seventh Framework Programme.
• The SMARTEES (Social Innovation Modelling Approaches to Realizing Transition to Energy Efficiency and Sustainability) project (2017-2021) was funded by the European Commission’s Horizon 2020 Programme.

Publications

Journals

• Jager, W.; Guijarro-Berdinas, B.; Bourman, L.; Antosz, P.; Alonso Betanzos, A.; Salt, D.; Polhill, G.; Rodrigues Arias, A.; Sanchez-Marono, N. (2024) Simulating the Role of Norms in Processes of Social Innovation: Three Case Studies, Journal of Artificial Societies and Social Simulation, 27(1), Art. 6
• Gonzalez-Redin, J.; Gordon, I.J.; Polhill, J.G.; Dawson, T.P.; Hill, R. (2024) Navigating Sustainability: Revealing Hidden Forces in Social–Ecological Systems, Sustainability, 16(3), Art. 1132
• Wijermans, N.; Scholz, G.; Chappin, E.; Heppenstall, A.; Filatova, T.; Polhill, G.; Semeniuk, C.; Stöppler, F. (2023) Agent decision-making: The Elephant in the Room – Enabling the justification of decision model fit in social-ecological models, Environmental Modelling & Software, 170, Art. 105850
• Antosz, P.; Birks, D.; Edmonds, B.; Heppenstall, A.; Meyer, R.; Polhill, G.; O’Sullivan, D.; Wijermans, N. (2023) What do you want theory for? – A pragmatic analysis of the roles of “theory” in agent-based modelling, Environmental Modelling & Software, 168, Art. 105802
• Polhill, G.; Heppenstall, A.; Heppenstall, A.; Batty, M.; Salt, D.; Colasanti, R.; Milton, R.; Hare, M. (2023) Exascale computing and next generation agent-based modelling, Review of Artificial Societies and Social Simulation
• Polhill, G.; Rouchier, J. (2023) Policy modelling requires a multi-scale, multi-criteria and diverse-framing approach. Lessons from a session at SocSimFest 2023, Review of Artificial Societies and Social Simulation
• Elsenbroich, C.; Polhill, J.G. (2023) Agent-based modelling as a method for prediction for complex social systems, International Journal of Social Research Methodology, 26(2), 133-142
• Polhill G.; Edmonds, B. (2023) Cognition and hypocognition: Discursive and simulation-supported decision-making within complex systems, Futures, 148, Art. 103121
• Polhill, G. (2022) Antisocial simulation using shared highperformance computing clusters to run agent-based models, Review of Artificial Societies and Social Simulation, 14 December 2022
• Davis, N.; Jarvis, A.; Polhill, J.G. (2022) Co-evolution of network structure and consumer inequality in a spatially explicit model of energetic resource acquisition, Physica A: Statistical Mechanics and its Applications, 608, Art. 128261
• Troost, C.; Bell, A. R.; van Delden, H.; Huber, R.; Filatova, T.; Le, Q. B.; Lippe, M.; Niamir, L.; Polhill, J. G.; Sun, Z.; Berger, T. (2022) How to keep it adequate: A protocol for ensuring validity in agent-based simulation, Environmental Modelling & Software, 159, Art. 105559
• Troost, C.; Bell, A. R.; van Delden, H.; Huber, R.; Filatova, T.; Le, Q. B.; Lippe, M.; Niamir, L.; Polhill, J. G.; Sun, Z.; Berger, T. (2022) How to keep it adequate: A protocol for ensuring validity in agent-based simulation, Environmental Modelling & Software, 159, Art. 105559
• Taghikhah, F.; Voinov, A.; Filatova, T.; Polhill, J.G. (2022) Machine-assisted agent-based modeling: opening the black box, Journal of Computational Science, 64, Art. 101854
• McCulloch, J.; Ge, J.; Ward, J.A.; Heppenstall, A.; Polhill, J.G.; Malleson, N. (2022) Calibrating Agent-Based Models Using Uncertainty Quantification Methods, Journal of Artificial Societies and Social Simulation, 25(2), Art. 1
• McCulloch, J.; Ge, J.; Ward, J.A.; Heppenstall, A.; Polhill, J.G.; Malleson, N. (2022) Calibrating Agent-Based Models Using Uncertainty Quantification Methods, Journal of Artificial Societies and Social Simulation, 25(2), Art. 1
• Antosz, P.; Szczepanska, T.; Bouman, L.; Polhill, J.G.; Jager, W. (2022) Sensemaking of causality in agent-based models, International Journal of Social Research Methods, 25(4), 557-567
• Reilly, J.A.; Dawson, T.P.; Matthews, R.B.; Smith, P.; Musk, C.C.; Potts, J.M.; Polhill, J.G. (2021) Projecting the effect of crop yield increases, dietary change and different price scenarios on land use under two different state security regimes., International Journal of Agricultural Sustainability,19(3-4), 288-304
• Polhill, J.G.; Hare, M.P.; Bauermann, T.; Anzola, D.; Palmer, E.; Salt, D.; Antosz, P. (2021) Using agent-based models for prediction in complex and wicked systems., Journal of Artificial Societies and Soicial Simulation, 24(3), Article No. 2
• Cohen, J.J.; Azarova, V.; Klöckner, C.A.; Kollmann, A.; Löfström, E.; Pellegrini-Masini, G.; Polhill, J.G.; Reichl, J.; Salt, D. (2021) Tackling the challenge of interdisciplinary energy research: A research toolkit., Energy Research and Social Sciences, 74, Article No. 101966
• Rivington, M.; King, R.; Duckett, D.; Iannetta, P.P.M.; Benton, T.G.; Burgess, P.J.; Hawes, C.; Wellesley, L.; Polhill, J.G.; Aitkenhead, M.; Lozada-Ellison, L.; Begg, G.; Williams, A.G.; Newton, A.C.; Lorenzo-Arribas, A.; Neilson, R.; Watts, C.; Harris, J.; Loades, K.; Stewart, D.; Wardell-Johnson, D.; Gandossi, G.; Udugbezi, E.; Hannam, J.A.; Keay, C. (2021) UK food and nutrition security during and after the COVID-19 pandemic., Nutrition Bulletin, 46(1), 88-97
• Ayllón, D.; Railsback, S.F.; Gallagher, C.; Augusiak, J.; Baveco, H.; Berger, U.; Charles, S.; Martin, R.; Focks, A.; Galic, N.; Liu, C.; van Loon, E.E.; Nabe-Nielsen, J.; Piou, C.; Polhill, J.G.; Preuss, T.G.; Radchuk, V.; Schmolke, A.; Stadnicka-Michalak, J.; Thorbek, P.; Grimm, V. (2021) Keeping modelling notebooks with TRACE: good for you and good for environmental research and management support., Environmental Modelling and Software, 136, Article No. 104932
• Ge, J.; Polhill, J.G.; Macdiarmid, J.; Fitton, N.; Smith, P.; Clark, H.; Dawson, T.; Aphale, M. (2021) Food and nutrition security under global trade: A relation-driven agent-based global trade model., Royal Society Open Science, 8(1) Article No. 201587
• Davis, N.A.; Polhill, J.G.; Aitkenhead, M.A. (2021) Measuring heterogeneity in soil networks: a network analysis and simulation-based approach., Ecological Modelling, 439, Article No. 109308
• Müller, B.; Hoffmann, F.; Heckelei, T.; Müller, C.; Hertel, T.W.; Polhill, J.G.; van Wilk, M.; Achterbosch, T.; Alexander, P.; Brown, C.; Kreuer, D.; Ewert, F.; Ge, J.; Millington, J.; Morley, T.; Seppelt, R.; Verburg, P.H.; Webber, H. (2020) Modelling food security: Bridging the gap between the micro and the macro scale., Global Environmental Change, 63, Article No. 102085.
• Barton, C.M.; Alberti, M.; Ames, D.; Atkinson, J-A.; Bales, J.; Burke, E.; Chen, M.; Diallo, S.Y.; Earn, D.J.D.; Fath, B.; Feng, Z.; Gibbons, C.; Hammond, R.; Hefferman, J.; Houser, H.; Hovmand, P.S.; Kopainsky, B.; Mabry, P.L.; Mair, C.; Meier, P.; Niles, R.; Nosek, B.; Osgood, N.; Pierce, S.; Polhill, J.G.; Prosser, L.; Robinson, E.; Rosenzweig, C.; Sankaran, S.; Stange, K.; Tucker, G. (2020) Call for transparency of COVID-19 models., Science, 368, 482-483.
• Squazzoni, F.; Polhill, J.G.; Edmonds, B.; Ahrweiler, P.; Antosz, P.; Scholz, G.; Chappin, É.; Borit, M.; Verhagen, H.; Giardini, F.; Gilbert, N. (2020) Computational models that matter during a global pandemic outbreak: A call to action., Journal of Artificial Societies and Social Simulation, 23, Article No. 10.
• Grimm, V.; Railsback, S.F.; Vincenot, C.; Berger, U.; Gallagher, C.; DeAngelis, D.L.; Edmonds, B.; Ge, J.; Giske, J.; Groeneveld, J.; Johnston, A.S.A.; Milles, A.; Nabe-Nielsen, J.; Polhill, J.G.; Radchuk, V.; Rohwäder, M.S.; Stillman, R.A.; Thiele, J.; Ayllón, D. (2020) The ODD protocol for describing agent-based and other simulation models: a second update to improve clarity, replication, and structural realism., Journal of Artificial Societies and Social Simulation, 23, Article No. 7.
• Davis, N.; Jarvis, A.; Aitkenhead, M.J.; Polhill, J.G. (2020) Trajectories towards maximum power and inequality in resource distribution networks., PLoS ONE, 15, Article No. e0229956.
• van Voorn, G.A.K.; Polhill, J.G.; Edmonds, B.; Hofstede, G.J. (2019) Editorial – Agent-based modelling for resilience., Ecological Complexity, 40, Article No. 100775.
• Gotts, N.M.; van Voorn, G.A.K.; Polhill, J.G.; de Jong, E.; Edmonds, B.; Hofstede, G.J.; Meyer, R. (2019) Agent-based modelling of socio-ecological systems: Models, projects and ontologies., Ecological Complexity, 40, Article No. 100728.

Books / chapters

• Antosz, P.; Jager, W.; Polhill, J.G.; Salt, D. (2021) Informing agent-based models of social innovation uptake., In: Rojas, I.; Gonzalo, J. & Català (eds.). Advances in Computational Intelligence, IWANN 2021. Lecture Notes in Computer Science, Volume 12862. Cham: Springer, Chapter 9, pp 105-117
• Polhill, J.G.; Salt, D.; Craig, T.; Wilson, R.; Colley, K. (2021) Sensitivity analysis of an empirical agent-based model of district heating network adoption, In: Rojas, I.; Gonzalo, J. & Català (eds.). Advances in Computational Intelligence. IWANN 2021. Lecture Notes in Computer Science, Volume 12862. Cham: Springer, pp 118-127
• Salt, D.A.; Polhill, J.G (2021) A NetLogo extension to secure data using GNUs Pretty Good Privacy Software Suite, In: Ahrweiler P. & Neumann M. (eds.). Advances in Social Simulation. ESSA 2019. Springer Proceedings in Complexity. Cham: Springer, pp 229-312
• Schlüter, M.; Lindkvist, E.; Wijermans, N.; Polhill, J.G. (2021) Agent-based modelling, In: Biggs, R., De Vos, A., Preiser, R., Clements, H., Maciejewski, K. & Schlüter, M. (eds.). The Routledge Handbook of Research Methods for Social-Ecological Systems. Abingdon: Routledge, Chapter 28, pp 383-397
• Ge, J.; Polhill, G. (2020) Agent-based models of coupled social and natural systems, In: Sang, N. (ed.) Modelling Nature-based Solutions: Integrating Computational and Participatory Scenario Modelling for Environmental Management and Planning. Cambridge University Press, 56-81
• Polhill, J.G.; Craig, T.; Alonso-Betanzos, A.; Sanchez-Marono, N.; Fontenla-Romero, O.; Dumitru, A.; Garcia-Mira, R.; Bonnes, M.; Bonaiuto, M.; Carrus, G.; Marricchiolo, F.; Fornara, F.; Ilin, C.; Steg, L.; Ruepert, A.; Keizer, K. (2017) Interactions matter. Modelling everyday pro-environmental norm transmission and diffusion in workplace networks., In: Alonso-Betanzos, A., Sánchez-Maroño, N., Fontenla-Romero, O., Polhill, J.G., Craig, T., Bajo, J. & Corchado, J.M. (eds.) Agent-Based Modeling of Sustainable Behaviors. Springer, Cham, Switzerland, Chapter 2, pp27-52.
• Grimm, V.; Polhill, J.G.; Touza, J. (2017) Documenting social simulation models: The ODD protocol as a standard. (Revised), In: Edmonds, B. & Meyer, R. (eds.). Simulating Social Complexity: A Handbook. 2nd edition. Springer, Berlin, pp349-365.
• Polhill, J.G.; Salt, D. (2017) The importance of ontological structure: why validation by ‘fit-to-data’ is insufficient., In: Edmonds, B. & Meyer, R. (eds.) Simulating Social Complexity: A Handbook. 2nd edition. Springer, 141-172.
• Sanchez-Maronon, N.; Alonso-Betanzos, A.; Fontenla-Romero, O.; Polhill, J.G.; Craig, T. (2017) Empirically-deprived behavioural rules in agent-based models using decision trees learned from questionnaire data., In: Alonso-Betanzos, A., Sanchez-Marono, N., Fontenla-Romera, O., Polhill, J.G., Craig, T., Bajo, J. & Corchado, M. (eds.). Agent Based Modelling of Sustainable Behaviors. Springer, Switzerland, Chapter 3, pp53-76.
• Ge, J.; Polhill, J.G. (2017) Preliminary results from an agent-based model of the daily commute in Aberdeen and Aberdeenshire, UK., In: Jager, W., Verbrugge R., Flache A., de Roo G., Hoogduin L. & Hemelrijk C. (eds.) Advances in Social Simulation 2015. Advances in Intelligent Systems and Computing 528. Springer, Cham., pp129-142.
• Polhill, J.G.; Gotts, N.M. (2017) How precise are the specifications of a psychological theory? Comparing implementations of Lindenberg and Steg’s Goal-Framing Theory of everyday pro-environmental behaviour., In: Jager, W., Verbrugge R., Flache A., de Roo G., Hoogduin L. & Hemelrijk C. (eds.) Advances in Social Simulation 2015. Advances in Intelligent Systems and Computing 528. Springer, Cham., 341-354.
• Polhill, J.G.; Milazzo, L.; Dawson, T.; Gimona, A.; Parker, D. (2017) Lessons learned replicating the analysis of outputs from a social simulation of biodiversity incentivisation., In: Jager, W., Verbrugge R., Flache A., de Roo G., Hoogduin L. & Hemelrijk C. (eds.) Advances in Social Simulation 2015. Advances in Intelligent Systems and Computing 528. Springer, Cham., 355-365.
• Sanchez-Maronon, N.; Alonso-Betanzos, A.; Fontenla-Romero, O.; Polhill, J.G.; Craig, T. (2015) Designing decision trees for representing sustainable behaviours in agents., In: Bajo, J., Hernandez, J.Z., Mathieu, P., Campbell, A., FernandezCaballero, A., Moreno, M.N., Julian, V., AlonsoBetanzos, A., JimenezLopez, M.D. & Botti, V. (eds.). Trends in Practical Applications of Agents, Multi-Agent Systems and Sustainability: The PAAMS Collection, Advances in Intelligent Systems and Sustainability, Springer, Berlin, Volume 372, 169-176.
• Grimm, V.; Polhill, J.G.; Touza, J. (2013) Documenting social simulation models: the ODD protocol as a standard., In: Edmonds, B. & Meyer, R. (eds.). Simulating Social Complexity: A Handbook. Springer, Berlin, Part II, pp117-133.
• Gimona, A.; Polhill, J.G.; Davies, B.B. (2011) Sinks, sustainability and conservation incentives., In: Sources, Sinks and Sustainability (eds. Liu, J., Hull, V., Morzillo, A., and Wiens, J). Cambridge University Press, Chapter 8, pp155-178.
• Gotts, N.M.; Polhill, J.G.; Law, A.N.R. (2010) Agent-based simulation in the study of social dilemmas., In: Gilbert, N. (ed.). Computational Social Science. SAGE Benchmarks in Social Research Methods Series, Volume 3. Sage Publications. ISBN-10: 1847871712, ISBN-13: 978-1847871718.
• Polhill, J.G. (2009) Agent-based modelling of socio-economic processes related to the environment: Example of land-use change., In: Baveye, P., Mysiak, J., Laba, M. (eds.). Uncertainties in Environmental Modelling and Consequences for Policy-Making. NATO Science for Peace and Security Series C – Environmental Security, Springer, 61-76. ISBN 978-90-481-2634
• Gotts, N.M.; Polhill, J.G. (2009) Narrative scenarios, mediating formalisms, and the agent-based simulation of land use change., In: Squazzoni, F. (ed.). Epistemological Aspects of Computer Simulation in the Social Sciences, Proceedings from 2nd International Workshop on Epistemological Perspectives on Simulation (EPOS), Brescia, Italy, 4-5 October 2006. Lecture Notes in Artificial Intelligence, Springer-Verlag, Berlin, 5466, 99-116.
• Pignotti, E.; Edwards, P.; Preece, A.; Gotts, N.M.; Polhill, J.G. (2008) Enhancing workflow with semantic descriptions of scientific intent., In: Goos, G., Hartmanis, J. & van Leeuwen (eds.). The Semantic Web: Research and Applications, 5th European Semantic Web Conference, Tenerife, Spain, 1-5 June 2008. Lecture Notes in Computer Science, 5021, Springer, Berlin, pp644-658.
• Parker, D.C.; Brown, D.G.; Polhill, J.G.; Deadman, P.J.; Manson, S.M. (2008) Ilustrating a new “conceptual design pattern” for agent-based models of land use via five case studies – the MR POTATOHEAD framework., In: Lopez Paredes, A. & Hernandez, I. Agent-Based Modelling in Natural Resource Management. INSISOC, Valladolid, Spain, 23-51
• Polhill, J.G.; Parker, D.C.; Gotts, N.M. (2007) Effects of land markets on competition between innovators and imitators in land use: results from FEARLUS-ELMM., In: Edmonds, B., Hernandez Iglesias, C. & Troitzsch, K.G. Social Simulation: Technologies, Advances and New Discoveries. Information Science Reference, London, Chapter 7, 81-97.

Technical / contract reports

• Polhill, G.; Ibrahim, A.; Sutherland, L. (2023) Transformative Land Use Change A position paper for the Macaulay Development Trust, International Land Use Study Centre Report, The James Hutton Institute, Aberdeen, UK.
• Gjefsen, M. D.; Burton, R.; Rønning, S.; Klöckner, C. A.; Helliwell, R.; Mittenzwei, K.; Campbell, H.; Polhill, G.; Roxburgh, N.; Vilhelmsen, K. (2023) Towards a cellular food future: Final recommendations from the Protein 2.0 project to Norwegian policy makers and food system actors, Technical Report N-1/23, Ruralis, Trondheim, Norway.
• Gjefsen, M. D.; Burton, R.; Rønning, S.; Klöckner, C. A.; Helliwell, R.; Mittenzwei, K.; Campbell, H.; Polhill, G.; Roxburgh, N.; Vilhelmsen, K. (2023) Towards a cellular food future: Final recommendations from the Protein 2.0 project to Norwegian policy makers and food system actors, Technical Report N-1/23, Ruralis, Trondheim, Norway.
• Polhill, G.; Rivington, M.; Duckett, D. (2021) Exploring COVID19 Food and Nutrition Security Plausible Scenario Narratives with the ‘FeedUs’ Model of Global Food Trade, Online.
• Rivington, M.; Duckett, D.; Iannetta, P.; Hawes, C.; Begg, G.; Polhill, G.; Loades, K.; Newton, A.; Aitkenhead, M.; Lozada-Ellison, L.; Neilson, R.; Gandossi, G.; Stewart, D.; Wardell-Johnson, D.; Udugbezi, E.; Lorenzo-Arribas, A.; Benton, T.; King, R., Burgess, P. (2021) An overview assessment of the COVID19 pandemic on the UK food and nutrition security, Online.
• Rivington, M.; King, R.; Duckett, D.; Iannetta, P.; G. Benton, T.; Burgess, P. J.; Hawes, C.; Wellesley, L.; Polhill, G.; Aitkenhead, M.; Lozada-Ellison, L. M.; Begg, G.; Williams, A. G.; Newton, A.; Lorenzo-Arribas, A.; Neilson, R.; Watts, C. (2021) UK Food and nutrition security during and after the COVID19 pandemic Project Report and Recommendations, The James Hutton Institute.
• Dumitru, A.; Lema Blanco, I.; Albulescu, P.; Antosz, P.; Bouman, L.; Colley, K.; Craig, T.; Jager, W.; Macsinga, I.; Meskovic, E.; Mischkowski, N.; Pellegrini Masini, G.; Polhill, G.; Quinti, G.; Salt, D.; Somervail, P.; Wilson, R. (2021) Policy recommendations for each cluster of casestudies Insights from policy scenario workshops, SMARTEES Deliverable 5.2.
• Pellegrini-Masini, G.; Albulescu, P.; Jager, W.; Löfström, E.; Macsinga, I.; Alonso-Betanzos, A.; Bouman, L.; Guijarro-Berdiñas, B.; Polhill, G.; Rodríguez-Arias, A.; Salt, D.; Sánchez-Maroño, N. (2021) Report on the updated theoretical framework for social innovation diffusion, SMARTEES Deliverable 6.2.
• Bouman, L.; Antosz, P.; Jager, W.; Polhill, G.; Salt, D.; Scalco, A.; Alonso-Betanzos, A.; Sánchez-Maroño, N.; Guijarro-Berdiñas, B.; Rodríguez-Arias, A. (2021) Report on scenario development and experiments for selected cases, SMARTEES: Updated Deliverable 7.4 (Final Report).
• Bouman, L.; Antosz, P.; Jager, W.; Polhill, G.; Salt, D.; Scalco, A.; Alonso-Betanzos, A.; Sánchez-Maroño, N.; Guijarro-Berdiñas, B.; Rodríguez-Arias, A. (2021) Report on scenario development and experiments for selected cases, SMARTEES: Updated Deliverable 7.4 (Final Report).
• Polhill, G.; Rivington, M.; Duckett, D. (2021) Exploring COVID19 Food and Nutrition Security Plausible Scenario Narratives with the FeedUs Model of Global Food Trade, The James Hutton Institute.
• Polhill, G.; Rivington, M.; Duckett, D. (2021) Exploring COVID19 Food and Nutrition Security Plausible Scenario Narratives with the FeedUs Model of Global Food Trade, The James Hutton Institute.
• Wilson R.; Colley, K.; Somervail, P.; Polhill, J.G.; Craig, T.; Salt, D.; Scalco, A.; Tiru, L-G.; Albulescu, P.; Macsinga, I.; Pellegrini-Masini, G.; Löfström, E.; Jager, W.; Antosz, P.; Bouman, L.; Dumitru, A. (2021) Integrated overview of choice behaviour and energy transitions in SMARTEES case studies, Report for SMARTEES Deliverable 4.2
• Antosz, P.; Jager, W.; Polhill, J.G.; Salt, D.; Scalco, A.; Alonso-Betanzos, A.; Sánchez-Maroño, N.; Guijarro-Berdiñas, B.; Rodríguez, A. (2020) SMARTEES simulation implementations for selected cases., SMARTEES Deliverable 7.3 (Report) , December 2020, 124pp.
• Polhill, J.G.; Craig, T.; Colley, K.; Ge, J.; Sat, D. (2018) The SMARTEES Project and The James Hutton Institute’s potential contribution to the Torry Heat Network project., Appendix 10.4 in support of Torry Heat Network, Report to be presented to Aberdeen City Council.
• Salt, D.; Polhill, J.G.; Craig, T. (2016) Deliverable 2.2: Report on the ontology generation and data and knowledge integration., Green Lifestyles Alternative Models and Up-scaling Regional Sustainability / GLAMURS EU SSH.2013.2.1-1 Grant Agreement No. 613420.
• Salt, D.; Polhill, J.G.; Craig, T. (2016) Deliverable 2., Report for Glamurs Ontology Project.
• Polhill, J.G.; Craig, T.; Ge, J.; Lorenzo-Arribas, A. (2016) Out-of-range wattage in CurrentCost energy monitor readings., Short Report to CurrentCost.
• Sutherland, L.A.; Gotts, N.M.; Polhill, J.G. (2006) CAVES: Complexity, agents, volatility, evidence and scale., Grampian Region Field Research Report. CAVES EU F6 Project.
• Matthews, R.B.; Gilbert, N.; Roach, A.; Polhill, J.G.; Gotts, N.M.; Izquierdo, L.R. (2005) Development of a rural economy and land use simulation modelling strategy., Final Project Report of RELU Development Activity RES-224-25-0102, Macaulay Institute, Craigiebuckler, Aberdeen AB158QH, UK.

Conference papers

• Chen, J.; Colley, K.; Craig, T.; Somervail, P.; Polhill, G.; Hague, A.; Wooldridge, T.; Martinez Sanchez, G.; Lorenzo-Arribas, A.; Roxburgh, N. (2024) Social Representation of Everyday Circularity: For a better understanding of ideas and practices of circular economy through second-hand purchasing, Presentation at the 28th International Conference Association of People-Environment Studies, 2-5 July 2024, Barcelona
• Hare, M.; Salt, D.; Colasanti, R. ; Milton, R.; Batty, M.; Heppenstall, A.; Polhill, G. (2024) Taking Agent-Based Social Simulation to the Next Level Using Exascale Computing Potential Use Cases, Capabilities Threats, Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024), N. Alechina, V. Dignum, M. Dastani, J.S. Sichman (eds.), Auckland, New Zealand, May 6-10 2024, IFAAMAS
• Salt, D.; Polhill, G.; Musk, C.; Milazzo, L.; Parker, D. (2023) Towards automated provenance collection for experimental runs of agent-based models, European Social Simulation Association Conference 2023, 4-8 September 2023, Glasgow
• Polhill, G.; McCormick, B. J. J. ; Roxburgh, N.; Heban, S.; Matthews, K. (2023) A Theory of the Middle Range to support food security and circular economy value chain scenario analysis, Social Simulation Conference 2023, University of Glasgow, UK, 4-8 September.
• Hare, M.; Roxburgh, N.; Salt, D.; Polhill, G. (2023) Barriers and model curation issues associated with rapid adaptation of empirical legacy ABM in response to urgent policy maker queries , Proceedings of the Social Simulation Conference 2023, 4-8 September 2023, Glasgow.
• Colley, K.; Craig, T.; Scholz, G.; Hague, A.; Wilson, R.; Polhill, G.; Salt, D.; Somervail, P.; Nazli Koseoglu, M.; Wooldridge, T. (2022) The role of individuals and households in the transition to a circular economy a social simulation approach, International Association of People-Environment Studies (IAPS) 2022 conference, online
• Polhill, G.; Matthews, K.; Ge, J.; Heppenstall, A.; Malleson, N. (2021) Exploring the effect of external influences of model parameterization, Social Simulation Conference 2021, Online, 20-24 September 2021.
• Salt, D.; Polhill, G.; Craig, T.; Wilson, R.; Colley, K.; Pinker, A.; Scalco, A.; Muhammad, M. (2021) Modelling coconstructed scnearios of district heat network adoption in Aberdeen, Social Simulation Conference 2021, Online, 20-24 September 2021.
• Polhill, J.G.; Salt, D.; Craig. T.; Wilson, R.; Colley, K. (2021) Sensitivity analysis of an empirical agent-based model of district heating network adoption., International Work Conference on Artificial Neural Networks, Online, 16-18 June 2021.
• Polhill, J.G. (2020) Linking ABM with energy system models: Feasibility, scale and scope., Energy Modelling Platform for Europe (EMP-E) 2020: Modelling Climate Neutrality for the European Green Deal, 6-8 October 2020. (Online)
• Hare, M.P.; Gimona, A.; Polhill, J.G. (2020) Contingent diachronicity and biodiversity: lessons from an agent-based model simulating the impact of biodiversity offsetting policy in a complex socio-ecological system., 10th International Congress on Environmental Modelling and Software, Brussels, Belgium, 14-18 September 2020, Session B2/B3.
• Parker, D.C.; Carro, A.; Detotto, C.; Filatova, T.; Ge, J.; Huang, Y.; Idda, C.; Magglioca, N.; Polhill, J.G.; Prunetti, D. (2019) MR POTATOHEAD: property market edition — development of a common description template and code base for agent-based land market models., Social Simulation Conference 2019, Johannes Gutenberg Universitaet Mainz, Germany, 23-27 September 2019.
• Salt, D.; Polhill, J.G. (2019) A NetLogo plug-in to secure data using GNUs pretty good privacy software suite., Social Simulation Conference (SSC 2019), Johannes Gutenberg University, Mainz, Germany, 23-27 September 2019.
• Polhill, J.G. (2019) Could a belief in the afterlife support the evolution of cooperation?, Social Simulation Conference 2019 (SSC2019), Johannes Gutenberg Universitaet, Mainz, Germany, 23-27 September 2019.
• Polhill, J.G.; Hare, M.; Anzola, D.; Bauermann, T.; French, T.; Post, H.; Perello Moragues, T.; Salt, D. (2019) Using ABMs for prediction: Two thought experiments and a workshop., Social Simulation Conference 2019 (SSC2019), Johannes Gutenberg Universitaet, Mainz, Germany, 23-27 September 2019.
• Polhill, J.G.; Ge, J.; Fitton, N.; Macdiarmid, J.; Matthews, R.B.; Dawson, T.; Clark, H.; Whybrow, S.; Aphale, M.; Smith P. (2019) Exploring scenarios affecting international food and nutrition security with an agent- based model of global trade., 4th Open Science Meeting of the Global Land Programme, Bern, Switzerland, 24-26 April 2019. (Talk)
• Poggio, L.; McLeod, J.; Castellazzi, M.; Compagnucci, A.; Gimona, A. (2018) Soil quality assessment in Scotland., 3rd Global Soil Security Conference, University of Sydney, Australia, 4-6 December 2018.
• Ge, J.; Polhill, J.G.; Macdiarmid, J.I.; Matthews, R.; Dawson, T.; Aphale, M. (2018) The impact of trade on food security – Preliminary results from an agent-based global trade model., Social Simulation Conference (SSC) 2018, Stockholm, Sweden, 20-24 August 2018
• Salt, D.A.; Polhill, J.G. (2018) Building NetLogo models from ontologies as a first step to model integration., Social Simulation Conference (SSC) 2018, Stockholm, Sweden, 20-24 August 2018, 12 pp.
• Polhill, J.G.; Gair, J.; Brewer, M.; Gotts, N.; Ge, J.; Butler, A. (2018) Comparing agent-based model versions using approximate bayesian computation., Social Simulation Conference (SSC) 2018, Stockholm, Sweden, 20-24 August 2018.
• Ge, J.; Polhill, J.G.; MacDiarmid, J.I.; Matthews, R.; Dawson, T.; Aphale, M. (2018) The impact of global food trade on food security and land use in the context of climate change – an empirical agent-based model., Landscape 2018, Berlin, Germany, 12-16 March 2018.
• Salt, D.; Polhill, J.G.; Barbet, V.; Wang, Y. (2017) Formalizing Callon’s theory of translation., Proceedings of SSC 2017-ESSA@work, Dublin, 25-29 September 2017. Afternoon Session Norms-GM, 27 September 2017.
• Polhill, J.G.; Burton, R.; Anders, K.; Ge, J. (2017) Using case-based reasoning as a basis to represent Bourdieu’s “forms of capital” for agricultural simulation., Social Simulation Conference 2017, Social Simulation for a Digital Society, University College Dublin, Ireland, 25 September 2017. Session Social Ecology – GM.
• Ge, J.; Polhill, J.G. (2017) Can succession, profitability, and off-farm income explain the polarization of cattle farms in Scotland? , Social Simulation Conference 2017, Social Simulation for a Digital Society, University College Dublin, Ireland, 25 September 2017.
• Ge, J.; Polhill, J.G.; Liu, N.; Roberts, D.; Craig, T. (2016) Modelling lifestyle and energy footprint in Europe’s ‘oil capital’ using an agent-based model., In: Sauvage, S., Sanchez-Perez, J.M., Rizzoli, A.E. (eds.). Proceedings of the 8th International Congress on Environmental Modelling and Software, Toulouse, France, 10-14 July 2016. Session A4: Modeling for Low carbon Economies, p253.
• Reilly, J.; Dawson, T.; Matthews, R.; Polhill, J.G.; Smith.P (2016) An agent-based model for studying the effects of sustainable intensification on food security in the nation state., International Environmental Modelling and Software Society (iEMSs), 8th International Congress on Environmental Modelling and Software, Toulouse, France, 10-14 July 2016. Paper, 11..
• Polhill, J.G.; Salt, D. (2016) Metrics of complexity from FEARLUS-SPOMM runs., CSoS Workshop, Hotel de Nieuwe Wereld, Wageningen, The Netherlands, 21-22 April 2016.
• Jin, X.; Robinson, K.; Lee, A.; Polhill, J.G.; Pritchard, C.; Parker, D. (2016) MIRACLE: A prototype cloud-based reproducible data analysis and visualization platform for outputs of agent-based models., GIScience 2016: The Ninth International Conference on Geographic Information Science, Montreal, Canada, 27-30 September 2016.
• Gonzalez, J.; Gordon, I.J.; Polhill, J.G.; Dawson, T.; Hill, R. (2015) Decoupling energy and natural resource use from economic growth: an agent-based modelling approach., MODSIM2015, 21st International Congress on Modelling and Simulation, Gold Coast Convention and Exhibition Centre, Broadbeach, Queensland, Australia, 29 November to 4 December 2015.
• Parker, D.; Barton, M.; Dawson, T.; Filatova, T.; Jin, X.; Lee, A.; Lee, J.-S.; Milazzo, L.; Pritchard, C.; Polhill, J.G.; Robinson, K.; Voinov, A. (2015) The MIRACLE project: Tools and analysis methods for output from agent-based models of coupled human-natural systems., The 2015 AMMCS-CAIMS Congress, Waterloo, Ontario, Canada, 7-12 June 2015.

Conference posters / abstracts

• Heppenstall, A.; Polhill, G.; Batty, M.; Salt, D.; Milton, R.; Hare, M.; Colasanti, R. (2024) Using HPC to model policy scenarios with agent-based models, Durham HPC Days 2024, 7-10 May 2024, Durham University, Department of Computer Science, Durham, UK
• Craig, T.; Colley, K.; Hague, A.; Chen, J.; Polhill, G.; Ge, J.; Salt, D. (2023) Modelling Circular Economy Behaviours: The Importance of Adequately Representing the Temporal Dimension (Slow down, you model too fast: The case for intentionally slow modelling), ICEP 2023 – International Conference on Environmental Psychology, 20-23 June 2023, Aarhus, Denmark
• Salt, D.; Polhill, G. (2023) Four Netlogo Extensions, Social Simulation Conference 2023, 4-8 September 2023, Glasgow
• Chen, J.; Craig, T.; Colley, K.; Hague, A.; Heban, S.; Somervail, P.; Wooldridge, T.; Martinez Sanchez, G.; Polhill, G.; Ballesteros Figueroa, A. (2023) Poster presentation in 2023 Social Simulation Conference, Social Simulation Conference 2023, 4-8 September 2023, Glasgow
• McCormick, B.; Macdiarmid, J.; Roxburgh, N.; Polhill, G. (2023) Simulating agriculture a midrange theory of everything (ish), Interdisciplinary Open Sessions Day, 13 October 2023, University of Aberdeen
• Roxburgh, N.; Polhill, G.; Gimona, A.; Hare, M.; Baggaley, N.; McCormick, B.; Macleod, K.; Rivington, M. (2023) Integrated socio-environmental modelling of policy scenarios, Conference poster.
• Polhill, G.; Heppenstall, A.; Batty, M.; Hare, M.; Salt, D.; Milton, R. (2023) Exascale agentbased modelling for policy evaluation in realtime (ExAMPLER), Social Simulation Conference 2023, University of Glasgow, UK, 4-8 September.
• Assefa, S.; Craig, T.; Hague, A.; Colley, K.; Chen, J.; Polhill, G. (2023) Using agent-based modelling to explore circular economy behaviours in Scotland, Social Simulation Conference 2023, University of Glasgow, UK, 4-8 September
• McCormick, B.; Roxburgh, N.; Polhill, G. (2023) Aligning agricultural subsidies with the production of healthy and sustainable diets, Livestock, Environment and People (LEAP) Conference 2022, 25 January 2023, Oxford.
• Salt, D.; Polhill, G.; Ball, J.; Gimona, A. (2022) Developing containerised automated workflows for large scale parallel execution of NetLogo models, iEMSs Conference 2022, 4 to 8 July 2022, Brussels, Belgium (Conference presentation, paper and extract).
• Roxburgh, N.; Polhill, G.; Ge, J. (2022) Recalibrating an agentbased model of global food and nutrition trade, iEMSs Biennial Meeting, 4-8 July 2022, Brussels.
• Polhill, G.; Baggaley, N.; Castellazzi, M.; Gimona, A.; Hare, M.; Ibiyemi, A.; Lilly, A.; Loades, K.; Macdiarmid, J.; Macleod, K.; McCormick, B.; McKeen, M.; Rivington, M.; Roxburgh, N.; Salt, D.; Smith, B.; Udugbezi, E.; Wang, C.; Wilkins, B. (2022) Developing agile approaches to scientific modelling in policyrelevant contexts, iEMSs 2022, 3-8 July 2022, Brussels, Belgium.
• Taghikhah, F.; Voinov, A.; Filatova, T.; Polhill, J. G. (2021) An interaction of computer and human intelligence in agent based modelling, MODSIM2021, 24th International Congress on Modelling and Simulation. Sydney, Australia, 5-9 December 2021.
• Colley, K.; Wilson, R.; Craig, T.; Polhill, G.; Salt, D.; Pinker, A.; Somervail, P. (2021) SMARTEES: Modelling household uptake of a city-wide district heat network in Aberdeen, Scotland. Virtual poster for Behavior, Environment and Climate Change Conference 2021, Virtual poster for Behavior, Environment and Climate Change Conference 2021, 8-10 November 2021, Online
• Polhill, J.G.; Salt, D.; Hare, M.; Macleod, K.; Athanasiadis, I.; Villa, F.; Edmonds, B.; Kocheril, G.; Bell, A. (2020) Integration first: Rethinking inter- and trans-disciplinary collaborations in modelling social-ecological systems., Tenth International Congress on Environmental Modelling and Software, Brussels, Belgium, 14-18 September 2020. (Online) (Abstract)
• Polhill, J.G.; Craig, T.; Salt, D.; Wilson, R. (2020) Simulating the dynamics of trust in one-off decisions such as joining a heat network., BEHAVE 2020: 6th European Conference on Behaviour and Energy Efficiency, Copenhagen, Denmark, 21-23 October 2020. Abstract.
• Müller, B.; Hoffmann, F.; Heckelei, T.; Müller, C.; Hertel, T. W.; Polhill, J.G.; van Wijk, M.; Achterbosch, T.; Alexander, P.; Brown, C.; Ge, J.; Millington, J.; Seppelt, R.; Verburg, P. H.; Webber, H. (2019) Modelling food security: bridging the gap between the micro and the macro scale., 4th Open Science Meeting of the Global Land Programme, Bern, Switzerland, 24-26 April 2019. Abstract.
• Polhill, J.G.; Ge, J.; Craig, T.; Salt, D.; Colley, K. (2018) Modelling fuel poverty and market failures., WICI Conference on Modelling Complex Urban Environments, St. Jerome’s College, University of Waterloo, Waterloo, Ontario, Canada, 21-22 June 2018. Abstract
• Polhill, J.G.; Ge, J.; Matthews, K.B.; Thomson, S. (2018) Exploring the factors influencing the polarization of cattle farms in Scotland., Landscape 2018: Frontiers of Agricultural Landscape Research, Berlin, Germany, 12-16 March 2018, p46. (Poster)
• Polhill, J.G.; Ge, J. (2018) Visualizing agent-based models: methods and challenges., Imaginative Tools for Visualizing Complexity, SEFARI Gateway Sponsored Workshop, James Hutton Institute, Dundee, 6 February 2018. (Poster)