The emergence of bluff in poker-like games
classification
⚛️ physics.soc-ph
physics.pop-ph
keywords
bluffbluffinggameslearningpoker-likeveryadaptiveagents
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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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