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A TWO‐STAGE WIN–WIN MULTIATTRIBUTE NEGOTIATION MODEL: OPTIMIZATION AND THEN CONCESSION
Author(s) -
Pan Li,
Luo Xudong,
Meng Xiangxu,
Miao Chunyan,
He Minghua,
Guo Xingchen
Publication year - 2013
Publication title -
computational intelligence
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.353
H-Index - 52
eISSN - 1467-8640
pISSN - 0824-7935
DOI - 10.1111/j.1467-8640.2012.00434.x
Subject(s) - negotiation , computer science , outcome (game theory) , interdependence , win win game , set (abstract data type) , key (lock) , operations research , mathematical optimization , management science , mathematical economics , microeconomics , economics , mathematics , computer security , political science , programming language , law
Many automated negotiation models have been developed to solve the conflict in many distributed computational systems. However, the problem of finding win–win outcome in multiattribute negotiation has not been tackled well. To address this issue, based on an evolutionary method of multiobjective optimization, this paper presents a negotiation model that can find win–win solutions of multiple attributes, but needs not to reveal negotiating agents’ private utility functions to their opponents or a third‐party mediator. Moreover, we also equip our agents with a general type of utility functions of interdependent multiattributes, which captures human intuitions well. In addition, we also develop a novel time‐dependent concession strategy model, which can help both sides find a final agreement among a set of win–win ones. Finally, lots of experiments confirm that our negotiation model outperforms the existing models developed recently. And the experiments also show our model is stable and efficient in finding fair win–win outcomes, which is seldom solved in the existing models.