A scalable method for online learning of non-linear preferences based on anonymous negotiation data

D.J.A. Somefun, J.A. Poutré, la

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

Samenvatting

We consider the problem of a shop agent negotiating bilaterally with many customers about a bundle of goods or services together with a price. To facilitate the shop agent's search for mutually beneficial alternative bundles, we develop a method for online learning customers' preferences, while respecting their privacy. By introducing extra parameters, we represent customers' highly nonlinear preferences as a linear model. We develop a method for learning the underlying stochastic process of these parameters online.
Originele taal-2Engels
TitelAutonomous agents and multiagent systems : Proceedings of the fifth international joint conference
UitgeverijAssociation for Computing Machinery, Inc
Pagina's417-419
ISBN van geprinte versie1-59593-303-4
StatusGepubliceerd - 2006
Evenement5th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), May 8–12, 2006, Hakodate, Japan - Hakodate, Japan
Duur: 8 mei 200612 mei 2006

Congres

Congres5th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), May 8–12, 2006, Hakodate, Japan
Verkorte titelAAMAS 2006
LandJapan
StadHakodate
Periode8/05/0612/05/06
AnderFifth International Joint Conference on Autonomous Agents and Multiagents Systems

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