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Multi-agent systems: which research for which applications

Identifieur interne : 000E30 ( Main/Exploration ); précédent : 000E29; suivant : 000E31

Multi-agent systems: which research for which applications

Auteurs : Eugénio Oliveira [Portugal] ; Klaus Fischer [Allemagne] ; Olga Stepankova [République tchèque]

Source :

RBID : ISTEX:CDC91FED038FACA2C454F73266754D23BAB98A9E

English descriptors

Abstract

For sometime now agent-based and multi-agent systems (MASs) have attracted the interest of researchers far beyond traditional computer science and artificial intelligence (AI). In this article we try to identify focal points of interest for researchers working in the area of distributed AI (DAI) and MAS as well as application-oriented researchers coming from related disciplines, e.g. electrical and mechanical engineering. We do this by presenting key research topics in DAI and MAS research and by identifying application domains in which the DAI and MAS technologies are most suitable. The research topics we discuss are separated into agent architectures and organisations, negotiation among agents, and self-adaptation of MAS using learning techniques. Regarding the application domains for these techniques we distinguish the application domains according to whether the agents control a physical or virtual body (Gestalt) or not. This separation of the application domains is not strict; it represents two ends of a continuum. On the one end of this continuum we have autonomous robot systems which act in a physical environment (sometimes referred to as hardware agents), and on the other end, we have abstract environments, such as in workflow systems, which rarely display the geometrical and physical aspects of the environment we are used to living in.

Url:
DOI: 10.1016/S0921-8890(98)00085-2


Affiliations:


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Le document en format XML

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<div type="abstract" xml:lang="en">For sometime now agent-based and multi-agent systems (MASs) have attracted the interest of researchers far beyond traditional computer science and artificial intelligence (AI). In this article we try to identify focal points of interest for researchers working in the area of distributed AI (DAI) and MAS as well as application-oriented researchers coming from related disciplines, e.g. electrical and mechanical engineering. We do this by presenting key research topics in DAI and MAS research and by identifying application domains in which the DAI and MAS technologies are most suitable. The research topics we discuss are separated into agent architectures and organisations, negotiation among agents, and self-adaptation of MAS using learning techniques. Regarding the application domains for these techniques we distinguish the application domains according to whether the agents control a physical or virtual body (Gestalt) or not. This separation of the application domains is not strict; it represents two ends of a continuum. On the one end of this continuum we have autonomous robot systems which act in a physical environment (sometimes referred to as hardware agents), and on the other end, we have abstract environments, such as in workflow systems, which rarely display the geometrical and physical aspects of the environment we are used to living in.</div>
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