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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 opponentsʼ behavior and to comply with the...
Persistent link: https://www.econbiz.de/10011049668
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...
Persistent link: https://www.econbiz.de/10011049875
This paper models the learning process of populations of randomly rematched tabula rasa neural network (NN) agents playing randomly generated 2×2 normal form games of all strategic classes. This approach has greater external validity than the existing models in the literature, each of which is...
Persistent link: https://www.econbiz.de/10011057436
Persistent link: https://www.econbiz.de/10011941942