Dynamic Programming — Policy Iteration & Value Iteration
Dynamic programming is RL with cheating. You already know the transition and reward functions; you just iterate the Bellman equation until `V` or `π` stops moving. It is the benchmark every sampling-based method tries to approach.
Visual edition planned
This lesson isn’t interactive yet.
It is part of the curriculum and will get the same treatment as Phase 1 — a visual cover, hands-on labs, derivations with numeric checks and a quiz. Until then, the original lesson is the best place to read it:
Part of Phase 09 — Reinforcement Learning. Use the previous / next cards below to keep browsing the phase.