Munich Personal RePEc Archive

Cold play: Learning across bimatrix games

Lensberg, Terje and Schenk-Hoppé, Klaus R. (2020): Cold play: Learning across bimatrix games.

There is a more recent version of this item available.
[thumbnail of MPRA_paper_104438.pdf]

Download (554kB) | Preview


We study one-shot play in the set of all bimatrix games by a large population of agents. The agents never see the same game twice, but they can learn `across games' by developing solution concepts that tell them how to play new games. Each agent's individual solution concept is represented by a computer program, and natural selection is applied to derive a stochastically stable solution concept. Our aim is to develop a theory predicting how experienced agents would play in one-shot games. To use the theory, visit https://gplab.nhh.no/gamesolver.php.

Available Versions of this Item

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.