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A text-based grid world framework for reinforcement learning agents to play around in. In general, the goal for the agent is to solve the maze in as few steps as possible. This is done using plenty of reinforcement learning algorithms including policy iteration, value iteration, sarsa, monte carlo methods, and iterative policy evaluation.

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