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Title

A multistage fuzzy decision approach for modelling adaptive negotiation strategies

Author(s)

Richter, Jan;  Klusch, Matthias;  Kowalczyk, Ryszard

Abstract

Automated bilateral agent negotiation under uncertainty, that is with imprecise or uncertain information about preferences, utilities and strategies of the opponent is known to be hard. In this paper, we present the first adaptive solution that bases on multistage fuzzy decision making. The modelling of individual preferences as fuzzy goal and fuzzy constraints, and observed strategic concession behaviour of opponents during negotiation as a fuzzy Markov decision process allows the agent to adapt its negotiation strategies and implied behaviour to improve its individual payoffs. In particular, we show that such adaptive bilateral negotiation strategies can be efficiently derived by an agent from negotiation threads of only two reference cases in its respectively maintained fuzzy transition matrix. Finally, we demonstrate the benefit of applying this solution to different soft-constrained negotiation settings by an initial comparative experimental evaluation.

Publication type

Conference paper

Research centre

Swinburne University of Technology. Faculty of Information and Communication Technologies. Centre for Complex Software Systems and Services

Source

Proceedings of the 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2010), held as part of the 2010 IEEE World Congress on Computational Intelligence (IEEE WCCI 2010), Barcelona, Spain, 18-23 July 2010, pp. 284-291

Publication year

2010

FOR Code(s)

010303 Optimisation;  0801 Artificial Intelligence and Image Processing;  080108 Neural, Evolutionary and Fuzzy Computation

Keyword(s)

Agent negotiation;  Decision algorithms;  Fuzzy decision approach

Publisher

IEEE

ISBN

9781424481262

Publisher URL

http://dx.doi.org/10.1109/FUZZY.2010.5584295

Copyright

Copyright © 2010 IEEE. Published version of the paper reproduced here in accordance with the copyright policy of the publisher. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Full text

Peer reviewed