A comparative study of game theoretic and evolutionary models for software agents
Most of the existing work in the study of bargaining behaviour uses techniques from game theory. Game theoretic models for bargaining assume that players are <i>perfectly rational</i> and that this rationality in <i>common knowledge</i>. However, the perfect rationality assum...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
2005-04.
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| Subjects: | |
| Online Access: | Get fulltext Get fulltext |
| Summary: | Most of the existing work in the study of bargaining behaviour uses techniques from game theory. Game theoretic models for bargaining assume that players are <i>perfectly rational</i> and that this rationality in <i>common knowledge</i>. However, the perfect rationality assumption does not hold for real-life bargaining scenarios with humans as players, since results from experimental economics show that humans find their way to the best strategy through trial and error, and not typically by means of rational deliberation. Such players are said to be <i>boundedly rational</i>. In playing a game against an opponent with bounded rationality, the most effective strategy of a player is not the equilibrium strategy but the one that is the best reply to the opponent's strategy. The evolutionary model provides a means for studying the bargaining behaviour of boundedly rational players. This paper provides a comprehensive comparison of the game theoretic and evolutionary approaches to bargaining by examining their assumptions, goals, and limitations. We then study the implications of these differences from the perspective of the software agent developer. |
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