| Abstract |
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This paper presents a model for integrative, one-to-one
negotiation in which the values across multiple attributes
are negotiated simultaneously. We model a mechanism in
which agents are able to use any amount of incomplete
preference information revealed by the negotiation partner
in order to improve the efficiency of the reached
agreements. Moreover, we show that the outcome of such a
negotiation can be further improved by incorporating a
"guessing" heuristic, by which an agent uses the history of
the opponent's bids to predict his preferences. Experimental
evaluation shows that the combination of these two
strategies leads to agreement points close to or on the
Pareto-efficient frontier. The main original contribution of
this paper is that it shows that it is possible for parties in a
cooperative negotiation to reveal only a limited amount of
preference information to each other, but still obtain
significant joint gains in the outcome.
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 Additional Information
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Citation:
Catholijn Jonker, Valentin Robu,
"Automated Multi-Attribute Negotiation with Efficient Use of Incomplete Preference Information,"
aamas,
pp. 1056-1063,
Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3 (AAMAS'04),
2004
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