Alonso, Eduardo, d'Inverno, Mark, Kudenko, Daniel, Luck, Michael and Noble, Jason (2001) Learning in multi-agent systems. Knowledge Engineering Review, 16 (3). pp. 277-284. ISSN 0269-8889Full text not available from this repository.
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.
|Additional Information:||Online ISSN 1469-8005|
|Subjects:||University of Westminster > Science and Technology > Electronics and Computer Science, School of (No longer in use)|
|Depositing User:||Users 4 not found.|
|Date Deposited:||02 Dec 2005|
|Last Modified:||15 Oct 2009 13:48|
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