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Tafl-ES: Exploring Evolution Strategies for Asymmetrical Board Games

Roberto Gallotta*

Roberto Capobianco

* External authors

AIxIA 2021

2021

Abstract

NeuroEvolution Strategies (NES) are a subclass of Evolution Strategies (ES). While their application to games and board games have been studied in the past [11], current state of the art in most of the games is still held by classic RL models, such as AlphaGo Zero [16]. This is despite recent work showing their desirable properties [12]. In this paper we use NES applied to the board game Hnefatafl, a known hard environment given its asymmetrical nature. In the experiment we set up we coevolve two populations of intelligent agents. With results collected thus far we show the validity of this approach and useful techniques to overcome its large computation resource and time requirements.

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