Efficient Algorithms for Learning to Play Repeated Games Against Computationally Bounded Adversaries

@inproceedings{Freund1995EfficientAF,
  title={Efficient Algorithms for Learning to Play Repeated Games Against Computationally Bounded Adversaries},
  author={Yoav Freund and Michael Kearns and Yishay Mansour and Dana Ron and Ronitt Rubinfeld and Robert E. Schapire},
  booktitle={FOCS},
  year={1995}
}
In the game theory literature, there is an intriguing line of research on the problem of playing a repeated matrix game against an adversary whose computational resources are limited in some way. Perhaps the main way in which this research differs from classical game theory lies in the fact that when our adversary is not playing the minimax optimal strategy for the game, we may be able to attain payoff that is significantly greater than the minimax optimum. In this situation, the correct… CONTINUE READING
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