Abstract
The issue that is addressed in this paper concerns the way interacting agents should understand their environment so that a common good used by the whole group would last. We synthesise the results of four models with agents interacting in artificial societies in which they have to share a resource. The four societies were built using multi-agent based simulation models that address issues related to the use of common renewable goods. The resources that are used by the artificial communities of agents are of two types: for some, agents must co-ordinate to exploit the resources; for others, the distribution of goods among agents is directly dependent on the distribution of the agents in space. But that classification cannot necessarily hold: the good use of the resources relies on an even distribution of agents in space, but this can be obtained with individual processes in some cases whereas in others it implies coordination too.
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References
Barreteau, O., Bousquet, F.: Shadoc: a multi-agent system to tackle viability of irrigated system. In: Annals of Operation research, Vol. 94 (2000) 139–162
Bonnefoy, J.L., Le Page, C., Rouchier, J., Bousquet, F.: Modelling spatial practices and social representations of space using multi-agent systems. In: Ballot, G., Weisbuch, G (eds) Applications of simulation to social sciences. Hermes (2000)
Bousquet, F.: Distributed artificial intelligence and object-oriented modelling of a fishery. In: Mathematical Computer Modelling, Vol. 2018 (1994) 97–107
Bousquet F., Le Page C., Bakam I., Takforyan A: A spatially explicit individualbased model of blue duikers population dynamics: multi-agent simulation of bushmeat hunting in an eastern cameroonian village. In: Ecological Modelling, in press (2000)
Conte, R., Castelfranchi, C.: Mind is not enough: the precognitive bases of social interaction. In: Gilbert, N., DOran, J.(eds), Simulating societies, UCL Press (1994) 267–286
Conte, R., Gilbert, N.: Computer Simulation for Social Theory. In: Conte, R., Gilbert, N. (eds) Artificial Societies. The Computer Simulation of Social Life, UCL Press, London (1995) 1–15
Conte, R., Castelfranchi C.: Distributed artificial intelligence and social science: critical issues. In: O’Hare, G.M.P., Jennings, N.R. (eds.), Foundations in Distributed Artificial Intelligence, Wiley Intersciences Publications (1996) 527–542
Costanza R.: What is ecological economics ?. In: Hall, C.A.S. (ed) Maximum power, the ideas and applications of H.T. Odum, University Press of Colorado (1995) 161–163
Doran, J.: Simulating Collective Misbelief, In: Journal of Artificial Societies and Social Simulation, Vol. 1, no.1 (1998)
Folse, L., Packard J., Grant W.: AI modelling of animal movements in a heterogenous habitat. Ecological modelling. Vol. 46 (1989) 57–72
Greif, A.: Reputation and Coalitions in Medieval Trade: Evidence on the Maghribi Traders. In: The journal of economic history, Vol XLIX,no. 4 (1989) 857–882
Haddadi A., Sundermeyer K.: Belief-Desire-Intention Agent architectures. In: O’Hare and Jennings (eds), Foundations of Distributed Artificial Intelligence, Wiley InterSciences (1996)
Hardin, G: The tragedy of the commons. In: Science, Vol. 162 (1968) 1243–1248
North, D.C.: Institutions, institutional change and economic performance, Cambridge University Press, Cambridge (1990)
Ostrom, E.: Governing the commons. The evolution of Institutions for collective action. Cambridge University Press, Cambridge (1990)
Requier-Desjardins, M.: L’accès aux pâturages, une approche économique de la mobilité, In: Actes du colloque Méga-Tchad, L’homme et l’animal dans le bassin du lac Tchad. Orstom, Paris (1997)
Rouchier, J., Barreteau, O., Bousquet, F.: Evolution and Coevolution of Individuals and Groups. In: Yves Demazeau (ed), Proceedings of the Third International Conference on Multi-Agent Systems, IEEE Los Alamitos, USA (1998) 254–260
Rouchier, J., Requier-Desjardins, M.: L’interdisciplinarité pour la modélisation dans la recherche-développement. Compte-rendu d’une experience en cours, une application au pastoralisme soudano-sahélien. Proceedings of SMAGET, Cemagref, Clermont-Ferrand (1998) 193–204
Rouchier, J., Bousquet, F., Requier-Desjardins, M., Antona, M.: A Multi-Agent model for describing transhumance in North Cameroon: comparison of different rationality to develop a routine. In: Journal for Economic Dynamic and Control, Vol. 25 (2001) 527–559
Takforyan, A.: La chasse: gestion communautaire et logique économique (Cameroun). In: Compagnon, D., Constantin, F. (eds), Karthala, Paris, Ifra, Nairobi (2000) 155–177
Williamson, O.E.: Les institutions de l’économie. Inter Editions, Paris (1994)
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Rouchier, J., Bousquet, F., Barreteau, O., Le Page, C., Bonnefoy, JL. (2000). Multi-Agent Modelling and Renewable Resources Issues: The Relevance of Shared Representations for Interacting Agents. In: Moss, S., Davidsson, P. (eds) Multi-Agent-Based Simulation. MABS 2000. Lecture Notes in Computer Science(), vol 1979. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44561-7_14
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DOI: https://doi.org/10.1007/3-540-44561-7_14
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