Adaptive negotiating agents in dynamic games: outperforming human behavior in diverse societies

Authors:
Eunkyung Kim;Luyan Chi;Yu Ning;Yu-Han Chang;Rajiv Maheswaran
Affiliations:
University of Southern California, Marina del Rey, CA;University of Southern California, Marina del Rey, CA;University of Southern California, Marina del Rey, CA;University of Southern California, Marina del Rey, CA;University of Southern California, Marina del Rey, CA
Venue:
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Year:
2012

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Abstract

Creating software agents that can negotiate effectively is an important problem that has been studied by agent researchers in contexts such as the trading agent competition and the virtual agents community. In the former, the goal is typically to find optimal policies in settings with uncertain and incomplete information, and where policies are typically evaluated in societies of entirely artificial agents [6]. In the latter, a goal is to create agents that can interact with humans --- in many cases, to train them in negotiation with individuals from particular cultures or different value settings [5].