Markov Decision Processes are the foundation of reinforcement learning. This interactive widget provides a hands-on simulation for understanding states, actions, rewards, and decision-making policies. Experiment with different scenarios and see how agents learn optimal strategies.
How to Use
Interact with the widget above to explore Markov Decision Processes. Configure the environment, set rewards, and observe how different policies affect the agent's behavior and learning process.
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