Learning opponent's preferences for effective negotiation: an approach based on concept learning
Autonomous Agents and Multi-Agent Systems
Strategies for avoiding preference profiling in agent-based e-commerce environments
Applied Intelligence
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This paper discusses multi-issue negotiation between agents such as providers and consumers in a group decision making environment. The outcome of such encounters depends on two key factors: the agenda (the set of issues associated with the service) and the negotiation procedure (how to settle the issues). In a multiple-issue negotiation process it is difficult to reach an optimal outcome when the two agents' preferences and the relative importance of the issues to them are not known to each other. This paper investigates the multi-issue decision making problem where preference information on issues associated with services are expressed in different formats by the consumers. A fuzzy preference concept is used to order the issues in the pre-negotiation stage to improve the efficiency of the outcome. Finally we propose an approach where the preference ordering is used in an agenda based multi-issue negotiation process for service level agreement.