Multi-agent simulations and ecosystem management: a review

This paper proposes a review of the development and use of multi-agent simulations (MAS) for ecosystem management. The use of this methodology and the associated tools accompanies the shifts in various paradigms on the study of ecological complexity. Behavior and interactions are now key issues for...

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Veröffentlicht in:Ecological modelling 2004-09, Vol.176 (3), p.313-332
Hauptverfasser: Bousquet, F, Le Page, C
Format: Artikel
Sprache:eng
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Zusammenfassung:This paper proposes a review of the development and use of multi-agent simulations (MAS) for ecosystem management. The use of this methodology and the associated tools accompanies the shifts in various paradigms on the study of ecological complexity. Behavior and interactions are now key issues for understanding and modeling ecosystem organization, and models are used in a constructivist way. MAS are introduced conceptually and are compared with individual-based modeling approaches. Various architectures of agents are presented, the role of the environment is emphasized and some computer tools are presented. A discussion follows on the use of MAS for ecosystem management. The strength of MAS has been discussed for social sciences and for spatial issues such as land-use change. We argue here that MAS are useful for problems integrating social and spatial aspects. Then we discuss how MAS can be used for several purposes, from theorization to collective decision-making support. We propose some research perspectives on individual decision making processes, institutions, scales, the credibility of models and the use of MAS. In conclusion we argue that researchers in the field of ecosystem management can use multi-agent systems to go beyond the role of the individual and to study more deeply and more effectively the different forms of organization (spatial, networks, hierarchies) and interactions among different organizational levels. For that objective there is considerably more fruit to be had on the tree of collaboration between social, ecological, and computer scientists than has so far been harvested.
ISSN:0304-3800
1872-7026
DOI:10.1016/j.ecolmodel.2004.01.011