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  Carles Sierra 1

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by Noyda Matos, Nick R. Jennings
http://www.ecs.soton.ac.uk/~nrj/download-files/noyda.ps
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Abstract:

To be successful in open, multi-agent environments, autonomous agents must be capable of adapting their negotiation strategies and tactics to their prevailing circumstances. To this end, we present an empirical study showing the relative success of different strategies against different types of opponent in different environments. In particular, we adopt an evolutionary approach in which strategies and tactics correspond to the genetic material in a genetic algorithm. We conduct a series of experiments to determine the most successful strategies and to see how and when these strategies evolve depending on the context and negotiation stance of the agent's opponent. 1.

Citations

582 The Evolution of Cooperation – Axelrod - 1984
396 The Evolution of Cooperation. Basic – Axelrod - 1984
185 Negotiation Decision Functions for Autonomous Agents – Faratin, Sierra, et al. - 1997
96 Negotiation and cooperation in multi-agent environments – Kraus - 1997
81 A service-oriented negotiation model between autonomous agents – Sierra, Faratin, et al. - 1997
62 Coevolutionary search among adversaries – Rosin - 1997
56 Genetic algorithms, tournament selection, and the effects of noise – Miller, Goldberg - 1995
54 A comparison of selection schemes used in genetic algorithms – Blickle, Thiele - 1995
9 On Artificial Agents for Negotiation in Electronic Commerce – Oliver - 1996
8 The emergence of cooperation in a society of autonomous agents - the prisoner's dilemma game under the disclosure of contract histories – Ito, Yano - 1995
5 Agent-based business process management. Int – Jennings, Faratin, et al. - 1996
2 Genetic Algorithms in Search, Optimisation and Matching Learning – Goldberg - 1989