Learning other agents' preferences in multi-agent negotiation using the bayesian classifier

Bui, H. H., Venkatesh, S. and Kieronska, D. 1999, Learning other agents' preferences in multi-agent negotiation using the bayesian classifier, International journal of cooperative information systems, vol. 8, no. 4, pp. 275-293.

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Title Learning other agents' preferences in multi-agent negotiation using the bayesian classifier
Author(s) Bui, H. H.
Venkatesh, S.
Kieronska, D.
Journal name International journal of cooperative information systems
Volume number 8
Issue number 4
Start page 275
End page 293
Total pages 19
Publisher World Scientific Publishing Co Pte Ltd
Place of publication Singapore
Publication date 1999
ISSN 0218-8430
1793-6365
Keyword(s) Cooperative problem solving
Machine learning
Multi-agent systems
Negotiation
Summary In multi-agent systems, most of the time, an agent does not have complete information about the preferences and decision making processes of other agents. This prevents even the cooperative agents from making coordinated choices, purely due to their ignorance of what others want. To overcome this problem, traditional coordination methods rely heavily on inter-agent communication, and thus become very inefficient when communication is costly or simply not desirable (e.g. to preserve privacy). In this paper, we propose the use of learning to complement communication in acquiring knowledge about other agents. We augment the communication-intensive negotiating agent architecture with a learning module, implemented as a Bayesian classifier. This allows our agents to incrementally update models of other agents' preferences from past negotiations with them. Based on these models, the agents can make sound predictions about others' preferences, thus reducing the need for communication in their future interactions.
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©1999, World Scientific Publishing Co
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044233

Document type: Journal Article
Collection: School of Information Technology
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