Detecting opponent concessions in multi-issue automated negotiation

Authors:
Scott Buffett;Luc Comeau;Bruce Spencer;Michael W. Fleming
Affiliations:
Institute for Information Technology - e-Business, Fredericton, New Brunswick, Canada;Institute for Information Technology - e-Business, Fredericton, New Brunswick, Canada;Institute for Information Technology - e-Business, Fredericton, New Brunswick, Canada;University of New Brunswick, Fredericton NB, Canada
Venue:
ICEC '06 Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet
Year:
2006

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Abstract

An agent engaged in multi-issue automated negotiation can benefit greatly from learning about its opponent's preferences. Knowledge of the opponent's preferences can help the agent not only to find mutually acceptable agreements more quickly, but also to negotiate deals that are better for the agent in question. In this paper, we describe a new technique for learning about an opponent's preferences by observing its history of offers in a negotiation. Patterns in the similarity between the opponent's offers and our own agent's offers are used to determine the likelihood that the opponent is making a concession at each stage in the negotiation. These probabilities of concession are then used to determine the opponent's most likely preference relation over all offers. Experimental results show that our technique significantly outperforms a previous method that assumes that a negotiation agent will always make concessions during the course of a negotiation.