Further towards a taxonomy of agent-based simulation models in environmental management

  • Authors:

  • M. Hare;P. Deadman

  • Affiliations:

  • Systemanalyse, Integrated Assessment und Modellierung Prozess, Swiss Federal Institute of Environmental Science and Technology, Duebendorf CH8600, Switzerland;Department of Geography, University of Waterloo, Waterloo, Ont., Canada N2L 3G1

  • Venue:
  • Mathematics and Computers in Simulation - Selected papers of the MSSANZ/IMACS 14th biennial conference on modelling and simulation
  • Year:
  • 2004

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Abstract

Agent-based simulation (ABS) is being increasingly used in environmental management. However, the efficient and effective use of ABS for environmental modelling is hindered by the fact that there is no fixed and clear definition of what an ABS is or even what an agent should be. Terminology has proliferated and definitions of agency have been drawn from an application area (Distributed Artificial Intelligence) which is not wholly relevant to the task of environmental simulation. This situation leaves modellers with little practical support for clearly identifying ABS techniques and how to implement them.This paper is intended to provide an overview of agent-based simulation in environmental modelling so that modellers can link their requirements to the current state of the art in the techniques that are currently used to satisfy them. Terminology is clarified and then simplified to two key existing terms, agent-based modelling and multi-agent simulation, which represent subtly different approaches to ABS, reflected in their respective artificial life (A-life) and distributed artificial intelligence roots. A representative set of case studies are reviewed, from which a classification scheme is developed as a stepping-stone to developing a taxonomy. The taxonomy can then be used by modellers to match ABS techniques to their requirements.