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Cliff Walking Exercise: Sutton's Reinforcement Learning 🤖

My implementation of Q-learning and SARSA algorithms for a simple grid-world environment.

The code involves visualization utility functions for visualizing reward convergence, agent paths for SARSA and Q-learning together with heat maps of the agent's action/value function.

Contents: ⭐

  • cliff_walking.py: Q-learning, SARSA, Visualization Functions
  • cliff_walking_report.pdf: Analysis on the Q-learning and SARSA algorithms

References: