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Factsheet: (Multi) Agent BAsed Modelling

 

Definition

An Agent Based Model is a specific individual based computational model for computer simulation extensively related to the theme in complex systems, emergence, Monte Carlo Method, computational sociology, multi agent systems, and evolutionary programming. The model was developed through a simple conceptual form in the late 1940s, and it took the advent of the microcomputer to really get up to speed. http://en.wikipedia.org/wiki/Agent_based_model

Application objectives

Simulate processes involving interacting objects sharing resources at the same time.

Pertinent participation process phase(s)

1. Starting organization
2. Actors analysis, context
3. Diagnostic of the current situation
4. Search of solutions
5. Implementation, evaluation

Application method

An agent is a computerized entity like a computer programme or a robot. An agent can be described as autonomous because it has the capacity to adapt when its environment changes. A multi-agent system is made up of a set of computer processes that occur at the same time, i.e. several agents that exist at the same time, share common resources and communicate with each other. The key issue in multi-agent systems is to formalize the coordination between agents. Research on agents, therefore, includes research into:

  • Decision-making : what decision-making mechanisms are available to the agent? What is the link between their perceptions, representations, and actions?
  • Control : what hierarchic relationships exist between agents ? How are they synchronized?
  • Communication : what kind of messages do they send each other? What syntax do these messages obey?

Application example(s)

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Example tools

A list of agent based models or frameworks is given at: http://www.agentlink.org/resources/agentprojects-db.php

AquaStress contact(s)

Ole Benjamin Schroeder, University of Osnabrueck (ole.schroeder@usf.uni-osnabrueck.de)

Nils Ferrand, Cemagref (nils.ferrand@cemagref.fr)

Reference

DeAngelis, D. L. and L. J. e. Gross,1992. Individual-based models and approaches in ecology, Chapman and Hall.

Deutschman, D. H., S. Levin, C. Devine, L. Buttel,1997. Scaling from trees to forests : analysis of a complex simulation model.

Ferber, J.,1999. Multi-Agent Systems : an Introduction to Distributed Artificial Intelligence. Reading, MA, Addison- Wesley.

Gilbert, N.,1995.. Emergence in social simulation. Artificial societies. The computer simulation of social life. R. c. a. N. Gilbert, UCL Press: 144-156.

Hogeweg, P. and B. Hesper,1990. Individual-oriented modelling in ecology. Mathl. Comput. Modelling 13: 83- 90.

Huston, M., D. DeAngelis, et al.,1988. New computer models unify ecological theory. Bioscience 38: 682-691.

Weiss, G., Ed. 1999. Multiagent Systems : a Modern Approach to Distributed Artificial Intelligence, MIT Press.