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Multi-agent Reinforcement Learning in OpenSpiel: A Reproduction Report

2021/02/27 by Michael Walton, Viliam Lisý, Walton, Michael +1 · 1 citation
Computer Science · #Artificial Intelligence in Games #Reinforcement Learning in Robotics #Evolutionary Algorithms and Applications

paper · pdf · doi:10.48550/arxiv.2103.00187

Abstract

In this report, we present results reproductions for several core algorithms implemented in the OpenSpiel framework for learning in games. The primary contribution of this work is a validation of OpenSpiel's re-implemented search and Reinforcement Learning algorithms against the results reported in their respective originating works. Additionally, we provide complete documentation of hyperparameters and source code required to reproduce these experiments easily and exactly.

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