Formalizing Risk Strategies and Risk Strategy Equilibrium in Agent Interactions Modeled as Infinitely Repeated Games

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4088)


To design intelligent agents for multi-agent applications, like auctions and negotiations, we need to first analyze how agents should interact in these applications. Game theory is a tool, which can be used. In game theory, decision-making often depends on probability and expected utility. However, decision makers usually violate the expected utility theory when there is risk in the choices. Instead, decision makers make decisions according to their attitudes towards risk. Also, reputations of other agents in making certain actions also affect decision-making. In this paper, we make use of risk attitude, reputation and utility for making decisions. We define the concepts of risk strategies, risk strategy equilibrium, and a formalized way to find the risk strategy equilibrium in infinitely repeated games. Simulations show that players get higher payoff by using risk strategies than using other game theoretic strategies.


Nash Equilibrium Game Theory Mixed Strategy Pure Strategy Intelligent Agent 
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-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringThe Chinese University of Hong Kong 

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