RL 1: Foundations — all 50 problems

Fifteen implementation exercises covering the computational core of reinforcement learning: discounted returns, the Bellman expectation and optimality equations, dynamic programming, temporal-difference learning and control, and modern policy-gradient objectives including GAE and PPO's clipped surrogate.