Negotiating agents that learn about others’ preferences
Bui, H. H., Kieronska, D. and Venkatesh, S. 1996, Negotiating agents that learn about others’ preferences, in Adaptation, coevolution and learning in multiagent systems : papers from the 1996 AAAI Symposium, AAAI Press, Menlo Park, Calif., pp. 16-21.
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 situation where communication is computationally costly or simply not desirable (e.g. to preserve the individual privacy).
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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