Abstract | ||
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Multi-Issue Negotiation protocols have been studied very widely and represent a promising field since most of negotiation problems in the real-world are complex ones including multiple issues. In particular, in reality issues are constrained each other. This makes agents' utilities nonlinear. There have been a lot of work on multi-issue negotiations. However, there have been very few work that focus on nonlinear utility spaces. In this paper, we assume agents have nonlinear utility spaces. For the linear utility domain, agents can aggregate the utilities of the issue-values by simple linear summation. In the real world, such aggregations are unrealistic. For example, we cannot just add up the value of car's tires and the value of car's engine when engineers design a car. In this paper, we propose an auction-based multiple-issue negotiation protocol among nonlinear utility agents. Our negotiation protocol employs several techniques, i.e., adjusting sampling, auction-based maximization of social welfare. Our experimental results show that our method can outperform the existing simple methods in particular in the huge utility space that can be often found in the real-world. Further, theoretically, our negotiation protocol can guarantee the completeness if some conditions are satisfied. |
Year | DOI | Venue |
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2008 | 10.3233/MGS-2008-4105 | Multiagent and Grid Systems |
Keywords | Field | DocType |
nonlinear utility agent,multi-issue negotiation,utilities nonlinear,multi-issue negotiation protocol,huge utility space,nonlinear utility space,nonlinear utility function,negotiation problem,linear utility domain,auction-based multiple-issue negotiation protocol,negotiation protocol,multi agent systems | Mathematical optimization,Nonlinear system,Computer science,Simulation,Multi-agent system,Sampling (statistics),Completeness (statistics),Maximization,Social Welfare,Distributed computing,Negotiation | Journal |
Volume | Issue | ISSN |
4 | 1 | 1574-1702 |
Citations | PageRank | References |
36 | 1.34 | 14 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Takayuki Ito | 1 | 888 | 380.66 |
Mark M. Klein | 2 | 1550 | 187.52 |
Hiromitsu Hattori | 3 | 222 | 25.09 |