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Social Simulation Bibliography

The James Hutton Institute has a long history of inter- and trans-disciplinary collaboration around agent-based models.

A selection of articles on agent-based modelling work done at The James Hutton Institute involving current and former employees is listed below. Open-access articles are indicated with an asterisk (*).

Models

Empirical

  • Dyer, G. A. and Nijnik, M. (2014) Implications of carbon forestry for local livelihoods and leakage. Annals of Forest Science 71 (2), 227-237. (doi:10.1007/s13595-013-0293-9)
  • * Ge, J. and Polhill, J. G. (2016) Exploring the combined effect of factors influencing commuting patterns and CO2 emissions in Aberdeen using an agent-based model. Journal of Artificial Societies and Social Simulation 19 (3), 11. http://jasss.soc.surrey.ac.uk/19/3/11.html (doi:10.18564/jasss.3078)
  • Ge, J., Polhill, J. G. and Craig, T. (2018) Too much of a good thing? Using a spatial agent-based model of transport to evaluate workplace sharing programs in Aberdeen. Journal of Transport Geography 69, 83-97. (doi:10.1016/j.jtrangeo.2018.04.005)
  • Ge, J., Polhill, J. G., Craig, T. and Liu, N. (2018) From oil wealth to green growth – An empirical agent-based model of recession, migration and sustainable urban transition. Environmental Modelling and Software 107, 119-140. (doi:10.1016/j.envsoft.2018.05.017)
  • * Ge, J., Polhill, J. G., Macdiarmid, J. I., Clark, H., Fitton, N., Smith, P. and Dawson, T. P. (2021) Food and nutrition security under global trade – a relation-driven agent-based global trade model. Royal Society Open Science 8 (1), 201587. (doi:10.1098/rsos.201587)
  • * Ge, J. Polhill, J. G., Matthews, K., Miller, D. and Spencer, M. (2018) Not one Brexit: How local context and social processes influence policy analysis: An agent-based model of Scottish cattle farms. PLoS ONE 13 (12), e0208451. (doi:10.1371/journal.pone.0208451)
  • Gonzalez-Redin, J., Gordon, I. J., Hill, R., Polhill, J. G. and Dawson, T. P. (2019) Exploring sustainable land use in forested tropical social-ecological systems: A case-study in the Wet Tropics. Journal of Environmental Management 231, 940-952. (doi:10.1016/j.jenvman.2018.10.079)
  • Gonzalez-Redin, J., Polhill, J. G., Dawson, T. P., Hill, R. and Gordon, I. J. (2020) Exploring sustainable development pathways in debt-based economies: The case of palm oil production in Indonesia. Ambio 49 (9), 1530-1548. (doi:10.1007/s13280-019-01286-8)
  • * Gotts, N. and Polhill, J. G. (2017) Experiments with a model of domestic energy demand. Journal of Artificial Societies and Social Simulation 20 (3), 11. http://jasss.soc.surrey.ac.uk/20/3/11.html (doi:10.18564/jasss.3467)
  • * Li, S., Gilbert, L., Harrison, P. A. and Rounsevell, M. D. A. (2016) Modelling the seasonality of Lyme disease risk and the potential impacts of a warming climate within the heterogeneous landscapes of Scotland. Journal of the Royal Society Interface 13 (116), 20160140. (doi:10.1098/rsif.2016.0140)
  • Neill, A., Tetzlaff, D., Strachan, N. J. C., Hough, R. L., Avery, L. M., Kuppel, S., Maneta, M. P. and Soulsby, C. (2020) An agent-based model that simulates the spatio-temporal dynamics of sources and transfer mechanisms contributing faecal indicator organisms to streams. Part 1: Background and model description. Journal of Environmental Management 270, 110903. (doi:10.1016/j.jenvman.2020.110903)
  • Neill, A., Tetzlaff, D., Strachan, N. J. C., Hough, R. L., Avery, L. M., Kuppel, S., Maneta, M. P. and Soulsby, C. (2020) An agent-based model that simulates the spatio-temporal dynamics of sources and transfer mechanisms contributing faecal indicator organisms to streams. Part 2: Application to a small agricultural catchment. Journal of Environmental Management 270, 110905. (doi:10.1016/j.jenvman.2020.110905)
  • Sánchez-Maroño, N., Alonso-Betanzos, A., Fontenla-Romero, O., Brinquis-Núñez, C., Polhill, J. G., Craig, T., Dumitru, A. and García-Mira, R. (2015) An agent-based model for simulating environmental behavior in an educational organization. Neural Processing Letters 42 (1), 89-118. (doi:10.1007/s11063-014-9390-5)
  • Scalco, A., Craig, T., Whybrow, S., Horgan, G. and Macdiarmid, J. (2020) Modelling the effects of social networks in interventions aimed at reducing meat consumption using a social simulation. Proceedings of the Nutrition Society 79 (OCE3). (doi:10.1017/S0029665120007697)
  • Scalco, A., Macdiarmid, J. I., Craig, T., Whybrow, S. and Horgan, G. W. (2019) An agent-based model to simulate meat consumption behaviour of consumers in Britain. Journal of Artificial Societies and Social Simulation 22 (4), 8. http://jasss.soc.surrey.ac.uk/22/4/8.html (doi:10.18564/jasss.4134)

Stylized, conceptual or theoretical

  • Davis, N., Aitkenhead, M. J. and Polhill, J. G. (2021) Measuring heterogeneity in soil networks: a network analysis and simulation-based approach. Ecological Modelling 439, 109308. (doi:10.1016/j.ecolmodel.2020.109308)
  • Gimona, A., Poggio, L., Polhill J. G. and Castellazzi, M. (2015) Habitat networks and food security: promoting species range shift under climate change depends on life history and the dynamics of land use choices. Landscape Ecology 30 (5), 771-789. (doi:10.1007/s10980-015-0158-8)
  • Gimona, A. and Polhill, J. G. (2011) Exploring robustness of biodiversity policy with a coupled metacommunity and agent-based model. Journal of Land Use Science 6 (2-3), 175-193. (doi:10.1080/1747423X.2011.558601)
  • Gimona, A., Polhill, G. and Davies, B. (2011) Sinks, sustainability and conservation incentives. In Liu, J., Hull, V., Morzillo, A. and Wiens, J. (eds.) Sources, Sinks and Sustainability. Cambridge University Press. pp. 155-178.
  • Polhill, J. G., Gimona, A. and Gotts, N. M. (2013) Nonlinearities in biodiversity incentive schemes: A study using an integrated agent-based and metacommunity model. Environmental Modelling and Software 45, 74-91. (doi:10.1016/j.envsoft.2012.11.011)

Methodology

  • Allyón, D., Railsback, S. F., Gallagher, C., Augusiak, J., Baveco, H., Berger, U., Charles, S., Martin, R., Focks, S., 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. and Grimm, V. (2021) Keeping modelling notebooks with TRACE: Good for you and good for environmental research and management support. Environmental Modelling & Software 136, 104932. (doi:10.1016/j.envsoft.2020.104932)
  • Edmonds, B. and Polhill, G. (2015) Open modelling in an age of complexity. In Terán, O. and Aguilar, J. (eds.) Societal Benefits of Freely Accessible Technologies and Knowledge Resources. IGI Global. pp. 237-254.
  • García-Mira, R., Dumitru, A., Alonso-Betanzos, A., Sánchez-Maroño, N., Fontenla-Romero, Ó., Craig, T. and Polhill, J. G. (2017) Testing scenarios to achieve workplace sustainability goals using backcasting and agent-based modeling. Environment and Behavior 49 (9), 1007-1037. (doi:10.1177/0013916516673869)
  • Grimm, V., Polhill, G. and Touza, J. (2017) Documenting social simulation models: The ODD protocol as a standard. In Edmonds, B. and Meyer, R. (eds.) Simulating Social Complexity: A Handbook, 2nd Edition. Cham: Springer. pp. 349-365. (doi:10.1007/978-3-319-66948-9_15)
  • * Grimm, V., Railsback, S. F., Vincenot, C. E., Berger, U., Gallagher, C., DeAngelis, D. L., Edmonds, B., Ge, J., Giske, J., Groenefeld, J., Johnston, A. S. A., Milles, A., Nabe-Nielsen, J., Polhill, J. G., Radchuk, V., Rohwäder, M.-S., Stillman, R. A., Thiele, J. C. and 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 (2), 7. http://jasss.soc.surrey.ac.uk/23/2/7.html (doi:10.18564/jasss.4259)
  • Polhill, J. G., Craig, T., Alonso-Betanzos, A., Sánchez-Maroño, N., Fontenla-Romero, O., Dumitru, A., García-Mira, R., Bonnes, M., Bonaiuto, M., Carrus, G., Maricchiolo, F., Fornara, F., Ilin, C., Steg, L., Ruepert, A. and 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. and Corchado, J. M. (eds.) Agent-Based Modeling of Sustainable Behaviors. Cham, Switzerland: Springer. pp. 27-52. (doi:10.1007/978-3-319-46331-5_2)
  • Polhill G. and Gotts N. (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. and Hemelrijk C. (eds.) Advances in Social Simulation 2015. Advances in Intelligent Systems and Computing 528. Cham: Springer. pp. 341-354. (doi:10.1007/978-3-319-47253-9_31)
  • Polhill G., Milazzo L., Dawson T., Gimona A. and 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. and Hemelrijk C. (eds.) Advances in Social Simulation 2015. Advances in Intelligent Systems and Computing 528. Cham: Springer. pp. 355-365. (doi:10.1007/978-3-319-47253-9_32)
  • * Polhill, G. and Salt, D. (2017) The importance of ontological structure: why validation by ‘fit-to-data’ is insufficient. In Edmonds, B. and Meyer, R. (eds.) Simulating Social Complexity: A Handbook, 2nd Edition. Cham: Springer. pp. 141-172 (doi:10.1007/978-3-319-66948-9_8) (Preprint on ResearchGate)
  • Sánchez-Maroño, N., Alonso-Betanzos, A., Fontenla-Romero, O., Polhill, J. G. and Craig, T. (2015) Designing decision trees for representing sustainable behaviours in agents. In Bajo, J., Hernández, J. Z., Mathieu, P., Campbell, A., Fernández-Caballero, A., Moreno, M. N., Julián, V., Alonso-Betanzos, A., Jiménez-López, M. D. and Botti, V. (eds.) Trends in Practical Applications of Agents, Multi-Agent Systems and Sustainability: The PAAMS Collection. Advances in Intelligent Systems and Computing 372. Switzerland: Springer. pp. 169-176. (doi:10.1007/978-3-319-19629-9_19)
  • Sánchez-Maroño, N., Alonso-Betanzos, A., Fontenla-Romero, O., Polhill, J. G. and Craig, T. (2017) Empirically-derived behavioral rules in agent-based models using decision trees learned from questionnaire data. In Alonso-Betanzos, A., Sánchez-Maroño, N., Fontenla-Romero, O., Polhill, J. G., Craig, T., Bajo, J. and Corchado, J. M. (eds.) Agent-Based Modeling of Sustainable Behaviors. Cham, Switzerland: Springer. pp. 53-76. (doi:10.1007/978-3-319-46331-5_3)

Tools and utilities

  • Jin, X., Robinson, K., Lee, A., Polhill, J. G., Pritchard, C. and Parker, D. (2017) MIRACLE: A prototype cloud-based reproducible data analysis and visualization platform for outputs of agent-based models. Environmental Modelling and Software 96, 172-180. (doi:10.1016/j.envsoft.2017.06.010)
  • * Polhill, J. G. (2015) Extracting OWL ontologies from agent-based models: A Netlogo extension. Journal of Artificial Societies and Social Simulation: Forum 18 (2), 15. http://jasss.soc.surrey.ac.uk/18/2/15.html (doi:10.18564/jasss.2810)

Reviews and strategic directions

  • Deffuant, G., Alvarez, I., Barreteau, O., de Vries, B., Edmonds, B., Gilbert, N., Gotts, N., Jabot, F., Janssen, S., Hilden, M., Kolditz, O., Murray-Rust, D., Rougé C. and Smits, P. (2012) Data and models for exploring sustainability of human well-being in global environmental change. The European Physical Journal Special Topics 214, 519-545. (doi:10.1140/epjst/e2012-01704-2)
  • Filatova, T., Polhill, J. G. and van Ewijk, S. (2016) Regime shifts in coupled socio-environmental systems: review of modelling challenges and approaches. Environmental Modelling and Software 75, 333-347. (doi:10.1016/j.envsoft.2015.04.003)
  • Ge, J. and Polhill, G. (2020) Agent based models of coupled social and natural systems. In Sang, N. S. (ed.) Modelling Nature-Based Solutions. Cambridge University Press. pp. 56-81. (doi:10.1017/9781108553827.003)
  • Gotts, N. M., van Voorn, G. A. K., Polhill, J. G., de Jong, E., Edmonds, B., Hofstede, G. J. and Meyer, R. (2019) Agent-based modelling of socio-ecological systems: Models, projects and ontologies. Ecological Complexity 40, 100728. (doi:10.1016/j.ecocom.2018.07.007)
  • Huber, R., Bakker, M., Balmann, A., Berger, T., Bithell, M., Britz, W., Brown, C., Grêt-Regamey, A., Hang, X., Le, Q. B., Mack, G., Meyfroidt, P., Millington, J., Müller, B., Polhill, J. G., Sun, J., Seidl, R., Troost, C. and Finger, R. (2018) Representation of decision-making in European agricultural agent-based models. Agricultural Systems 167, 143-160. (doi:10.1016/j.agsy.2018.09.007)
  • * Lee, J.-S., Filatova, T., Ligmann-Zielinska, A., Hassani-Mahmooei, B., Stonedahl, F., Lorscheid, I., Voinov, A., Polhill, G., Sun, Z. and Parker, D. (2015) The complexities of agent-based modeling analysis. Journal of Artificial Societies and Social Simulation 18 (4), 4. http://jasss.soc.surrey.ac.uk/18/4/4.html (doi:10.18564/jasss.2897)
  • Müller, B., Balbi, S., Buchmann, C. M., de Sousa, L., Dressler, G., Groeneveld, J., Klassert, C. J., Le, Q. B., Millington, J. D. A., Nolzen, H., Parker, D. C., Polhill, J. G., Schlüter, M., Schulze, J., Schwarz, N., Sun, Z., Taillandier, P. and Weise, H. (2014) Standardised and transparent model descriptions for agent-based models: Current status and prospects. Environmental Modelling and Software 55, 156-163. (doi:10.1016/j.envsoft.2014.01.029)
  • Müller, B., Hoffmann, F., Heckelei, T., Müller, C., Hertel, T. W., Polhill, J. G., van Wijk, M., Achterbosch, T., Alexander, P., Brown, C., Kreuer, D., Ewert, F, Ge, J., Millington, J. D. A., Seppelt, R., Verburg, P. and Webber, H. (2020) Modelling food security: Bridging the gap between the micro and the macro scale. Global Environmental Change 63, 102085. (doi:10.1016/j.gloenvcha.2020.102085)
  • Polhill, J. G., Filatova, T., Schlüter, M. and Voinov, A. (2016) Modelling systemic change in coupled socio-environmental systems. Environmental Modelling and Software 75, 318-332. (doi:10.1016/j.envsoft.2015.10.017)
  • * Polhill, J. G., Ge, J., Hare, M. P., Matthews, K. B., Gimona, A., Salt, D. and Yeluripati, J. (2019) Crossing the chasm: a ‘tubemap’ for agent-based social simulation of policy scenarios in spatially-distributed systems. Geoinformatica 23 (2), 169-199 (doi:10.1007/s10707-018-00340-z)
  • * Squazzoni, F., Polhill, J. G., Edmonds, B., Ahrweiler, P., Antosz, P., Scholz, G., Chappin, É., Borit, M., Verhagen, H., Giardini, F. and Gilbert, N. (2020) Computational models that matter during a global pandemic outbreak: A call to action. Journal of Artificial Societies and Social Simulation 23 (2), 10. http://jasss.soc.surrey.ac.uk/23/2/10.html (doi:10.18564/jasss.4298)

Research

Areas of Interest


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The James Hutton Research Institute is the result of the merger in April 2011 of MLURI and SCRI. This merger formed a new powerhouse for research into food, land use, and climate change.