Bluffing and betting behavior in a simplified poker game

A pure‐strategy, simplified poker (PSP) game is proposed, where two players draw from a small and discrete number of hands. Equilibrium strategies of the game are described and an experiment is conducted where 120 subjects played the PSP against a computer, which was programmed to play either the equilibrium solution or a fictitious play (FP) learning algorithm designed to take advantage of poor play. The results show that players did not adopt the cutoff‐type strategies predicted by the equilibrium solution; rather they made considerable “errors” by: Betting when they should have checked, checking when they should have bet, and calling when they should have folded. There is no evidence that aggregate performance improved over time in either condition although considerable individual differences were observed among subjects. Behavioral learning theory (BLT) cannot easily explain these individual differences and cognitive learning theory (CLT) is introduced to explain the apparent anomalies. Copyright © 2009 John Wiley & Sons, Ltd.