Recent advances in the field of Distributed Artificial Intelligence (DAI) and more and more powerful microcomputers are raising the level of interest in multi-agents systems for various kinds of applications. This is particularly true in Natural Resources Management (NRM) as multi-agents systems constitute powerful tools for studying interactions between societies and their environment. They can also provide solutions for scaling issues.
A multi-agents system is composed of a set of agents evolving in a common environment. These agents communicate and interact. The system is characterized by its structures as well as its control and communication methods. These artificial multi-agents systems are the subject of research in informatics. They use computers or networks of computers to develop metaphors (social, biological, physical) expressing a vision of the real world as sets of interacting entities. Finally, they provide a way to simulate complex real situations, phenomena or organizations.
Development of the multi-agents systems approach is closely related to the problem of complexity (multiple scales and organization levels, multiple agents and viewpoints, etc.) and the related search for simple representations of the real world through modelling. For sustainable NRM, identifying the conditions that allow the co-viability of environmental / resources dynamics on the one hand and socio-economic dynamics on the other hand is seen more and more as a key issue. By focusing on the interactions between various agents (individual of collective, each one having a certain autonomy) that are acting in a given environment, the multi-agents systems approach seems well adapted to dealing with this core problem.
Objectives:
- To provide an introduction to multi-agents systems (MAS) and a review of the state of the art in applying MAS to several key scientific disciplines, with an emphasis on NRM issues,
- To allow participants to develop their own first simple MAS application by constructing and operating a MAS on a topic of their choice,
- To identify future opportunities for developing the use and application of the MAS approach to key NRM issues in the region.