What is Reinforcement Learning?Taxonomy of RL Methods History of Reinforcement Learning

Multi-Armed Bandits MDP and Dynamic Programming Monte Carlo and Temporal Difference Q-Learning DQN DQN Improvements

Policy Gradient Theorem and REINFORCE TRPO PPO RL for Sequence Generation and RLHF

Actor-Critic Framework DDPG TD3 and SAC

Dyna and Learned Models Model Predictive Control AlphaZero and MuZero

Imitation Learning Offline RL Exploration Goal-Conditioned RL Multi-Agent RL

Model-Based RL

Dyna and Learned Models

Integrated learning, planning, and acting with learned environment dynamics.

Placeholder content for Dyna and Learned Models.

TD3 and SAC

Twin Delayed DDPG and Soft Actor-Critic with maximum entropy RL.

Model Predictive Control

MPC, MBPO, and planning with learned models for sample-efficient RL.