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What is Reinforcement Learning?

Taxonomy of RL Methods

Multi-Armed Bandits

Markov Decision Processes

Dynamic Programming

Monte Carlo and Temporal-Difference Prediction

Sarsa and Q-Learning

Deep Q-Networks

DQN Improvements

Policy Gradient and REINFORCE

Actor-Critic, A2C and A3C

Off-Policy Policy-Based Framework

Dyna and Learned Models

Model Predictive Control

AlphaZero and MuZero

RLHF and Language Models

Imitation Learning

Goal-Conditioned RL

Model-BasedAlphaZero and MuZero

AlphaZero and MuZero

Planning with Monte Carlo tree search and learned models.

To be done soon

Model Predictive Control

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

RLHF and Language Models

RLHF for autoregressive language models, from reward modeling and PPO to DPO and GRPO alternatives.