Learning other agents' preferences in multiagent negotiation
Bui, H. H., Kieronska, D. and Venkatesh, S. 1996, Learning other agents' preferences in multiagent negotiation, in AAAI-96 : Proceedings of the 13th National Conference on Artificial Intelligence, AAAI, Menlo Park, Calif., pp. 114-119.
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Learning other agents' preferences in multiagent negotiation
In multiagent systems, an agent does not usually have complete information about the preferences and decision making processes of other agents. This might prevent the agents from making coordinated choices, purely due to their ignorance of what others want. This paper describes the integration of a learning module into a communication-intensive negotiating agent architecture. The learning module gives the agents the ability to learn about other agents' preferences via past interactions. Over time, the agents can incrementally update their models of other agents' preferences and use them to make better coordinated decisions. Combining both communication and learning, as two complement knowledge acquisition methods, helps to reduce the amount of communication needed on average, and is justified in situations where communication is computationally costly or simply not desirable (e.g. to preserve the individual privacy).
ISBN
9780262510912 026251091X
Language
eng
Field of Research
089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective
970108 Expanding Knowledge in the Information and Computing Sciences
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