The emergence of bluff in poker-like games

Physics – Physics and Society

Scientific paper

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In a slightly different version, this article is a chapter of the Ph.D. thesis of Andrea Guazzini

Scientific paper

We present a couple of adaptive learning models of poker-like games, by means
of which we show how bluffing strategies emerge very naturally, and can also be
rational and evolutively stable. Despite their very simple learning algorithms,
agents learn to bluff, and the best bluffing player is usually the winner.

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