Melioration Learning in Two-Person Games.
Where this comes from
- Record sourced from PubMed, PMID 27851815.
- Also identified by DOI 10.1371/journal.pone.0166708 and PMC identifier 5112854.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
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.
Medical subject headings
- Game Theory
- Learning
- Reinforcement, Psychology