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Fernando Lopes, Nuno Mamede, A. Q. Novais, Helder Coelho
Autonomous agents are being used in an increasingly number of applications. These agents operate in complex environments and, over time, conflicts inevitably occur among them. Conflict resolution is crucial for achieving coordination. The predominant process for resolving conflicts is negotiation. Recent growing interest in electronic commerce has also given increased importance to negotiation. Artificial intelligence researchers have recently started to investigate the design of autonomous negotiating agents. Some researchers developed or adopted a model of individual behavior and used the model as a starting point for the development of a negotiation model. However, most researchers have focused solely on developing negotiation models. They have addressed only part of the overall task of building autonomous negotiating agents. In particular, they have paid little attention to the problem of integrating existing or new models of individual behavior with their negotiation models. This fundamental problem is still an open problem. This paper presents a generic negotiation model for autonomous agents that handles multi-party, multi-issue, and single or repeated rounds. The main components of the model are: (i) a prenegotiation model, (ii) a negotiation protocol, (iii) an individual model of the negotiation process, (iv) a set of negotiation strategies, and (v) a set of negotiation tactics. The model is based on computationally tractable assumptions, accounts for a tight integration of the individual capability of planning and the social capability of negotiation, and formalizes a set of human negotiation procedures. The paper also introduces the type of real world applications we are interested in, by describing a multi-agent supply chain system.
Keywords: Multi-Agent Systems, Negotiation, E-Commerce, Conflict Management, Autonomous Agents
Citation: Fernando Lopes, Nuno Mamede, A. Q. Novais, Helder Coelho: Negotiation Strategies for Autonomous Computational Agents. In R.López de Mántaras and L.Saitta (eds.): ECAI2004, Proceedings of the 16th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2004, pp.33-37.
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