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Automated Negotiating Agent Based on Evolutionary Stable Strategies

  • Akiyuki Mori
  • Takayuki Ito
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 614)

Abstract

Bilateral multi-issue closed bargaining problems are critical in the research field of automated negotiations. In this paper, we propose a negotiating agent that is based on the expected utility value at the equilibrium point of an evolutionary stable strategy (ESS). Furthermore, we show the evaluation results of negotiating simulations, and demonstrate that our agent outperforms existing agents under the negotiation rules of the 2014 International Automated Negotiating Agents Competition (ANAC2014). Our paper has three contributions. First, our agent derives the expected utility of the ESS equilibrium points based on dividing a negotiation into two phases, and realizes the appropriate concession by the concession function that incorporates it. Second, it can reduce time discounts by a quick compromise based on an appropriate lower limit of concession value. Third, it can get beneficial results of negotiation simulations by the proposed concession function under various negotiation conditions.

Keywords

Ultimatum Game Evolutionary Stable Strategy Negotiation Strategy Bargaining Problem Time Discount 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Nagoya Institute of TechnologyAichiJapan

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