**Author**:
Krelle, Wilhelm**Title**: Learning in a Class of Non-Zero-Sum Two-Person Games Part I**Abstract**: We consider a finite two person game where the players move in turn.
Neither player knows the payoffs of the other, but each player has an
a-priori-probability distribution for the possible "types" of his opponent
and is able to form an opinion of this a-priori-probability of his opponent.
Each player follows the Bayesian rule of maximizing his payoff expectation.
"Learning" in this context means that a player narrows down the possible
"types" of his opponent by observing and analyzing his moves in the course
of the game. Thus he is able to correct his a-priori-probabilities and to
improve his decisions. Asymptotically he may know exactly against whom he is
playing.
It is shown that a unique solution results which under certain conditions
converges to the subgame perfect Nash equilibrium point of the game under
perfect information.**Keywords**:
**JEL-Classification-Number**:**Creation-Date**: May 1991

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