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vectorized-environments

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A Double Deep Q-Network (DDQN) reinforcement learning algorithm to train a Battlesnake agent. Several features are used to enhance the algorithm, including vectorized environments, prioritized experience replay, board canonicalization, self-play, and a Monte Carlo Tree Search.

  • Updated Sep 11, 2026
  • Python

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