The predictive power of Cumulative Prospect Theory (CPT) and Expected Utility Theory (EUT) is typically compared using decisions from description (DfD), wherein lotteries' outcome values and probabilities are explicitly stated. In decisions from experience (DfE), individuals sample (without...

This paper examines strategic adaptation in participants’ behavior conditional on the type of their opponent. Participants played a constant-sum game for 100 rounds against each of three pattern-detecting computer algorithms designed to exploit regularities in human behavior such as...

This paper aspires to fill a conspicuous gap in the literature regarding learning in games — the absence of empirical verification of learning rules involving pattern recognition. Weighted fictitious play is extended to detect two-period patterns in opponents’ behavior and to comply with the...

This paper models the learning process of a population of randomly-rematched tabula rasa neural network agents playing randomly generated 3 × 3 normal form games of all strategic types. Evidence was found of the endogenous emergence of a similarity measure of games based on the number and types...

Belief models capable of detecting 2- to 5-period patterns in repeated games by matching the current historical context to similar realizations of past play are presented. The models are implemented in a cognitive framework, ACT-R, and vary in how they implement similarity-based categorization...

The question of whether, and if so how, learning can be transferred from previously experienced games to novel games has recently attracted the attention of the experimental game theory literature. Existing research presumes that learning operates over actions, beliefs or decision rules. This...