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

Advanced Topics

Goal-Conditioned RL

Hindsight Experience Replay and learning to reach arbitrary goals.

Placeholder content for Goal-Conditioned RL.

Exploration

Curiosity-driven exploration with Random Network Distillation and Intrinsic Curiosity Module.

Multi-Agent RL

Cooperative and competitive multi-agent learning, MADDPG, QMIX, and communication.