bellman

Master the mathematical skeleton of reinforcement learning. Learn how the agent-environment loop formalizes decision-making, why the Markov property is the key assumption, and how Bellman expectation equations link policies to value functions.

When you know the full MDP model, dynamic programming finds the optimal policy exactly. Learn the Bellman optimality equation, the contraction argument that guarantees convergence, and the concrete difference between policy iteration and value iteration — with a value-iteration code walkthrough.