Learning in multi-agent systems

In recent years, multi-agent systems (MASs) have received increasing attention in the artificial intelligence community. Research in multi-agent systems involves the investigation of autonomous, rational and flexible behaviour of entities such as software programs or robots, and their interaction an...

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Bibliographic Details
Published in:Knowledge engineering review 2001-09, Vol.16 (3), p.277-284
Main Authors: ALONSO, EDUARDO, D'INVERNO, MARK, KUDENKO, DANIEL, LUCK, MICHAEL, NOBLE, JASON
Format: Article
Language:English
Subjects:
Algorithms
Computer science
Hypotheses
Intelligence
Logic programming
Machine learning
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Summary:In recent years, multi-agent systems (MASs) have received increasing attention in the artificial intelligence community. Research in multi-agent systems involves the investigation of autonomous, rational and flexible behaviour of entities such as software programs or robots, and their interaction and coordination in such diverse areas as robotics (Kitano et al., 1997), information retrieval and management (Klusch, 1999), and simulation (Gilbert & Conte, 1995). When designing agent systems, it is impossible to foresee all the potential situations an agent may encounter and specify an agent behaviour optimally in advance. Agents therefore have to learn from, and adapt to, their environment, especially in a multi-agent setting.
ISSN:0269-8889
1469-8005
DOI:10.1017/S0269888901000170