Evolving Chess-like Games Using Relative Algorithm Performance Profiles

3 Apr

Paper presented as talk at EvoGAMES 2016 in Porto (Portugal).

Jakub Kowalski, Marek Szykula


We deal with the problem of automatic generation of complete rules of an arbitrary game. This requires a generic and accurate evaluating function that is used to score games. Recently, the idea that game quality can be measured using differences in performance of various gameplaying algorithms of different strengths has been proposed; this is called Relative Algorithm Performance Profiles. We formalize this method into a generally application algorithm estimating game quality, according to some set of model games with properties that we want to reproduce.
We applied our method to evolve chess-like boardgames. The results show that we can obtain playable and balanced games of high quality.



Enjoy it!


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