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Project: Deep Q-Learning Agent

· 2 min read

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Python Gymnasium Reinforcement Learning Group Project Last Updated

Overview​

  • Created a Gym environment of a simple third-person shooter game in Python
  • Implemented a simple Deep-Q Network with PyTorch to train agents to master at the game (left image)
  • Fine-tuned the hyperparameters of the agent, achieving average kill streak of 7 (right image, top) and lengthend the survival duration by 4 times (right image, bottom), which significantly better than the random baseline of 0.22 kills on average.
  • Explored how deep-Q learning models handle a variable quantity of moving objects, i.e. the bullets and enemies, and relevant adjustments to the reward functions and representations of the observation space needed.

Report: Report