A situated agent-based model to reveal irrigators' options behind their actions under institutional arrangements in Southern France
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collective irrigation
agent-based model
situated action
institutional arrangement

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Richard, B., Bonte, B., Barreteau, O., & Braud, I. (2022). A situated agent-based model to reveal irrigators’ options behind their actions under institutional arrangements in Southern France. Socio-Environmental Systems Modelling, 3, 17893. https://doi.org/10.18174/sesmo.17893


There has been little exploration of the explicit simulation of the set of options of actors in agent-based models and its evolution over time. This study proposes to use affordances as intermediate entities between agents' environment and agent actions. We illustrated the approach on a typical gravity-fed network in the South-East of France to explore how the abandonment of traditional sharing of water changes the irrigators' options to irrigate. We simulated a typical dry year irrigation season under two institutional arrangements (i.e. traditional coordination through daily slots and its abandonment). Simulation results are consistent with field surveys, and reveal an increase in the number of internal conflicts among irrigators as the counterpart of the abandonment of traditional sharing of water. They also highlight the consequences of the heterogeneity of the irrigators' interests within the collective institution. The sensitivity analysis of the model allowed identification of optimal modalities of coordination, and a potential compromise between past and current institutional arrangements. The key benefits of using affordances in ABM lie in the study of their population dynamics for characterizing the interaction situations between actors and their environment and for better understanding the model dynamics.

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Afoutni, Z., Courdier, R. & Guerrin, F. (2014). A Multiagent System to Model Human Action Based on the Concept of Affordance. Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2014), Aug 2014, Vienne, Austria, pp. 664-651,hal-01466931.

Afoutni, Z. (2015). Un modèle multi-agents pour la representation de l’action située basée sur l’affordance et la stigmergie. PhD Thesis, University of La Réunion, Saint-Denis.

Bommel, P., Bécu, N., Le Page, C., & Bousquet, F. (2016). Cormas: an agent-based simulation platform for coupling human decisions with computerized dynamics. In T. Kaneda, H. Kanegae, Y. Toyoda, & P. Rizzi (Eds.), Simulation and Gaming in the Network Society (pp. 387–410). Singapore: Springer. https://doi.org/10.1007/978-981-10-0575-6_27

Bousquet, F., Bakam, I., Proton, H., & Le Page, C. (1998). Cormas: common-pool resources and multi-agent systems. In Tasks and Methods in Applied Artificial Intelligence (pp. 826–837). The 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA-98-AIE Benicàssim, 1–4 June 1998, Castellón, Spain. https://doi.org/10.1007/3-540-64574-8_469

Bousquet, F., & Le Page, C. (2004). Multi-agent simulations and ecosystem management: a review. Ecological Modelling, 176, 313–332. https://doi.org/10.1016/j.ecolmodel.2004.01.011

Chemero, A. (2003). An outline of a theory of affordances. Ecological Psychology, 15, 181-95.

Clancey, W. (2002). Simulating activities: relating motives, deliberation and attentive DailySlots. Cognitive Systems Research, 3, 471-499.

Cornwell, J.B., O’Brien, K., Silvermanet, B.G. & Toth, J.A. (2003). Affordance theory for improving the rapid generation, composability, and reusability of synthetic agents and objects. In Proceedings of the 12th BRIMS Conference, Behavior Representation in Modeling and Simulation, May 2003, 12 pages.http://repository.upenn.edu/ese_papers/291.

Daydé, C., Couture, S., Garcia, F. & Martin-Clouaire, R. (2014). Investigating Operational Decision-Making in Agriculture. In 2014 International Environmental Modelling andSoftware Society (iEMSs), San Diego, USA. International Environmental Modelling andSoftware Society (iEMSs).

Dreyfus, H.L. (1972). What Computers Can't Do. A Critique of Artificial Reason. New York: Harper and Row. Revised edition (1979). Augmented edition (1992), What Computers Still Can't Do. Cambridge, MA: MIT Press.

Ferber, J. (1999). Multi-Agent System: An Introduction to Distributed Artificial Intelligence. Harlow: Addison Wesley Longman, ISBN 0-201-36048-9.

Filatova, T., Verburg, P.H., Parker, D.C. & Stannard, C.A. (2013). Spatial agent-based models for socio-ecological systems: challenges and prospects. Environmental Modelling & Software, 45, 1-7.

Forrester, J. W. (1968). Market Growth as Influenced by Capital Investment. Sloan Management Review, 9(2), 83-105.

Gibson, J.J. (1977). The theory of affordances. In R. Shaw & J. Brandsford (éds.) Perceiving, Acting, and Knowing. Toward an Ecological Psychology, Hillsdale: Lawrence Erlbaum Associates.

Gibson, J.J. (1986). The Ecological Approach to visual perception. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. (Original work published in 1979).

Gleizes, M.-P., Camps, V., Karageorgos, A., & Di Marzo Serugendo, G. (2011). Agents and multi-agent systems. In G. Di Marzo Serugendo, M.-P. Gleizes, & A. Karageorgos (Eds.), Self-organising Software: from natural to artificial adaptation, pp. 105–119. Berlin, Germany: Springer-Verlag.

Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S.K., Huse, G., Huth, A., Jepsen, J.U., Jørgensen, C., Mooij, W.M., Müller, B., Pe’er, G., Piou, C., Railsback, S.F., Robbins, A.M., Robbins, M.M., Rossmanith, E., Rüger, N., Strand, E., Souissi, S., Stillman, R.A., Vabø, R., Visser, U. & DeAngelis, D.L. (2006). A standard protocol for describing individual-based and agent-based models. Ecological Modelling, 198, 115-126.

Grimm, V., Berger, U., DeAngelis, D. L., Polhill, J. G., Giske, J., & Railsback, S. F. (2010). The ODD protocol: a review and first update. Ecological Modelling, 221, 2760–2768. https://doi.org/10.1016/j.ecolmodel.2010.08.019

Guerrin, F., Afoutni, Z., & Courdier, R. (2016). Agent-based modeling: What matters is action. In The 8th International Congress on Environmental Modelling and Software Society, iEMSs, pp. 412-419. Toulouse, France.

Harris, S. G. (1990). The fifth discipline: The art and practice of the learning organization. By Peter Senge, New York: Doubleday/Currency, 1990. Human Resource Management, 29, 343-348. DOI: 10.1002/hrm.3930290308.

Johnston, R.B. & Brennan, M. (1996). Planning or organizing: The implications of theories of activity for management of operations. Omega, 24(4), 367-384.

Jones, H.G., 1992. Plants and Microclimate. 2nd edn (Cambridge: Cambridge University Press), pp.428.

Letcher, R.A, Jakeman, A.J., Barreteau, O., Borsuk, M.E., ElSawah, S., Hamilton, S.H., Henriksen, H.J, Kuikka, S., Maier, H.R., Rizzoli, A.E, van Delden, H. & Voinov, A. (2013). Selecting among five common modelling approaches for integrated environmental assessment and management. Environmental Modelling & Software, 47, 159-181. https://doi.org/10.1016/j.envsoft.2013.05.005.

Lee, J.S., Filatova, T., Liegmann-Zielinska, A., Hassani-Mahmooei, B., Stonedahl, F., Lorscheid, I., Voinov, A., Polhill, G., Sun. Z. & Parker, C.D. (2015). The complexities of agent-base modeling output analyzing. Journal of Artificial Societies and Social Simulation, 18(4), 4. DOI: 10.18564/jasss.289

Loubier, S. & Garin, P. (2013). Un avenir incertain pour les associations syndicales autorisées d’irrigation. Sciences Eaux et Territoires, 11(2), 90–95.

Loubier, S., Ruf T. & Garin P. (2019). France. In: Molle F, Sanchis-Ibor C, Avella-Reus L, eds. Irrigation in the Mediterranean. Global Issues in Water Policy 22. 2019, pp. 123–149. Available from https://doi.org/10.1007/978-3-030-03698-0.

Luyat, M. & Regia-Corte, T. (2009). Les affordances: de James Jerome Gibson aux formalisations récentes du concept. L’Année psychologique, 109, 297-332.

Malaterre, P-O. (2008). Control of Irrigation Canals: why and how? In : Proceedings of the International Workshop on Numerical Modelling of Hydrodynamics for Water Resources, Centro Politecnico Superior, University of Zaragoza Spain, June 18-21 2007, p. 271-292, Taylor & Francis (Balkema Ed.).

Martin-Clouaire, R. (2017). Modelling Operational Decision-Making in Agriculture. Agricultural Science. 8: 527-544.

Merot, A., Bergez, J-E., Capillon, A. & Wery, J. (2008). Analysing farming practices to develop a numerical, operational model of farmers’ decision-making processes: An irrigated hay cropping system in France. Agricultural Systems, 98(2):108-118, https://doi.org/10.1016/j.agsy.2008.05.001.

Papasimeon, M. (2009). Modelling Agent-Environment Interaction in Multi-Agent Simulations with Affordances. Phd Thesis, The University of Melbourne, Australia.

Plusquellec, H. (1988). Improving the Operation of Canal Irrigation Systems. Washington D.C., The Economic Development Institute of the World Bank and the Agriculture and the Rural Department, mars 1988.

Richard, B. (2020). Coupling agent-based and agro-hydrological modeling to represent human actions within an agro-hydrosystem. Application to collective irrigation in the Buëch catchment (France). Hydrology. Institut agronomique, vétérinaire et forestier de France, 2020. English.

Richard, B., Bonte, B., Barreteau, O. & Braud, I. (2020). The abandonment of water daily slot and its operational consequences on collective irrigated systems. A situational multi-agent approach applied to a gravity-fed canal of Middle-Durance (France). La Houille Blanche, 4, 43-55. https://doi.org/10.1051/lhb/2020033.

Reynaud, A. (2009). Adaptation à court et à long terme de l’agriculture au risque de sécheresse: une approche par couplage de modèles biophysiques et économiques. Revue d’Etudes en Agriculture etEnvironnement - Review of agricultural and environmental studies, INRA Editions, 90, pp.121-154.

Sanchis-Ibor, C. & Molle, F. (2019). Introduction. In Molle, F., Sanchis-Ibor, C., Avellà-Reus, L. (eds) Irrigation in the Mediterranea. Global Issues in Water Policy 22, Springer. pp. 1-14.

Sequeira, P., Vala, M., & Paiva, A. (2007). What can I do with this?: Finding possible interactions between characters and objects. AAMAS ’07: Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems.

Simone, M. (2011). Repenser la notion d'affordance dans ses dynamiques sémiotiques. In: Intellectica. Revue de l'Association pour la Recherche Cognitive, n°55, 2011/1. Synesthésie et Intermodalité. pp. 241-267

Stoeffregen, T. A. (2003). Affordances as properties of the animal-environment system. Ecological Psychology, 15, 115-34.

Suchman, L. (1987). Plans and situated actions: the problem of human/machine communication. Cambridge: Cambridge University Press.

Turvey, M.T. (1992). Affordances and prospective control: An outline of the ontology. Ecological Psychology, 4, 173-87.

Vidal, J.-P., Martin, E., Franchistéguy, L., Baillon, M. & Soubeyroux, J.M. (2010). A 50-year high-resolution atmospheric reanalysis over France with the Safran system. International Journal of Climatology, 30(11), 1627-1644. DOI: 10.1002/joc.2003.10.1002/joc.2003.

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Copyright (c) 2021 Bastien Richard, Bruno Bonté, Olivier Barreteau, Isabelle Braud