Deep Reinforcement Learning, Demystified: From Q‑Learning and DQNs to PPO, MuZero, and RLHF
If you’ve ever stared at a maze of RL algorithms and wondered where to start—or how to actually make any of it work in practice—you’re not alone. Reinforcement learning can feel intimidating: math-heavy, compute-hungry, and littered with subtle pitfalls. Yet it’s also one of the most exciting ways to build agents that learn by doing,…