This project builds a reinforcement learning agent to navigate the classic 4x4 grid world environment. The agent was made to learn an optimal policy through Q-Learning which allowed it to take actions to reach a goal while avoiding obstacles. The environment and the agent were built to be compatible with OpenAI Gym environments.
rspai/Atari_game_reinforcement_learning
Implementation of Atari game using reinforcement learning
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