Better-reply dynamics with bounded recall
A Zapechelnyuk - Mathematics of Operations Research, 2008 - pubsonline.informs.org
Mathematics of Operations Research, 2008•pubsonline.informs.org
A decision maker is engaged in a repeated interaction with Nature. The objective of the
decision maker is to guarantee to himself the average payoff as large as the best-reply
payoff to Nature's empirical distribution of play, no matter what Nature does. The decision
maker with perfect recall can achieve this objective by a simple better-reply strategy. In this
paper we demonstrate that the relationship between perfect recall and bounded recall is not
straightforward: The decision maker with bounded recall may fail to achieve this objective …
decision maker is to guarantee to himself the average payoff as large as the best-reply
payoff to Nature's empirical distribution of play, no matter what Nature does. The decision
maker with perfect recall can achieve this objective by a simple better-reply strategy. In this
paper we demonstrate that the relationship between perfect recall and bounded recall is not
straightforward: The decision maker with bounded recall may fail to achieve this objective …
A decision maker is engaged in a repeated interaction with Nature. The objective of the decision maker is to guarantee to himself the average payoff as large as the best-reply payoff to Nature's empirical distribution of play, no matter what Nature does. The decision maker with perfect recall can achieve this objective by a simple better-reply strategy. In this paper we demonstrate that the relationship between perfect recall and bounded recall is not straightforward: The decision maker with bounded recall may fail to achieve this objective, no matter how long his recall and no matter what better-reply strategy he uses.
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