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Melioration learning in two-person games

Melioration learning is an empirically well-grounded model of reinforcement learning. By means of computer simulations, this paper derives predictions for several repeatedly played two-person games from this model. The results indicate a likely convergence to a pure Nash equilibrium of the game. If no pure equilibrium exists, the relative frequencies of choice may approach the predictions of the mixed Nash equilibrium. Yet in some games, no stable state is reached.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa.de:bsz:15-qucosa-213943
Date23 November 2016
CreatorsZschache, Johannes
ContributorsUniversität Leipzig, Fakultät für Sozialwissenschaften und Philosophie, Public Library of Science,
PublisherUniversitätsbibliothek Leipzig
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typedoc-type:article
Formatapplication/pdf
SourcePLoS ONE 11(11): e0166708 doi:10.1371/journal.pone.0166708

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