This paper presents AgentFSEGA experience at the Automated Negotiation Agents Competition 2010. AgentFSEGA is a time-constrained negotiation strategy that learns the opponent's profile out of its moves. Having at the baseline the Bayesian negotiation strategy [3], AgentFSEGA considers the negotiation time as a resource, being prepared to concede more as time passes. While AgentFSEGA performs well on relatively large domains, we prove that the performance of the negotiation strategy does not downgrade significantly even for small, engineered, domains not suited for a learning strategy.
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