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arXiv · 2212.14104

Towards automating Codenames spymasters with deep reinforcement learning

Sherman Siu
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Abstract

Although most reinforcement learning research has centered on competitive games, little work has been done on applying it to co-operative multiplayer games or text-based games. Codenames is a board game that involves both asymmetric co-operation and natural language processing, which makes it an excellent candidate for advancing RL research. To my knowledge, this work is the first to formulate Codenames as a Markov Decision Process and apply some well-known reinforcement learning algorithms such as SAC, PPO, and A2C to the environment. Although none of the above algorithms converge for the Codenames environment, neither do they converge for a simplified environment called ClickPixel, except when the board size is small.

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Sherman Siu. 2022-12-28. Towards automating Codenames spymasters with deep reinforcement learning. https://arxiv.org/abs/2212.14104

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