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Abstract
The paper presents a model of heuristic negotiation between self-interested agents which allows the use of arguments, negotiation over multiple issues of the negotiation object, single and multi-party negotiation, and learning of the agent's negotiation primitives. The model uses negotiation objects and negotiation frames to separate the object of negotiation from the negotiation process. In order to negotiate strategically, the agents use a reinforcement learning algorithm applied on a specific state space representation of the negotiation process.
Index
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References
Bibliographical reference
Adina Magda Florea and Eugenia Kalisz, « A Negotiation Learning Model for Open Multi-Agent Environments », CASYS, 20 | 2008, 121-130.
Electronic reference
Adina Magda Florea and Eugenia Kalisz, « A Negotiation Learning Model for Open Multi-Agent Environments », CASYS [Online], 20 | 2008, Online since 03 September 2024, connection on 06 June 2025. URL : http://popups.uliege.be/3041-539x/index.php?id=2839
Authors
Adina Magda Florea
Department of Computer Science, University "Politehnica" of Bucharest, Spl.Independentei 313, Bucharest, Romania
Eugenia Kalisz
Department of Computer Science, University "Politehnica" of Bucharest, Spl.Independentei 313, Bucharest, Romania
