Deep RL


OVERVIEW of methods and papersCS 285
Imitation LearningCS 224RCS 285
RL IntroductionCS 285
RL Basic TheoryCS 234Reviewed 2024
The Key DistributionsCS 234CS 285Reviewed 2024
MDP and Bellman TheoryCS 234TabularValue
Model-Based Tabular ControlCS 234TabularValue
Model-Free Policy EvaluationCS 234TabularValue
Model-Free ControlCS 234TabularValue
Policy Search (policy gradient)CS 234CS 285PolicyReviewed 2024
Advanced Policy SearchCS 234CS 285PolicyReviewed 2024
Actor Critic AlgorithmsCS 285Reviewed 2024
Value Function MethodsCS 234CS 285Reviewed 2024Value
Linear Analysis of Value Function MethodsCS 234CS 285Value
Optimal Control & PlanningCS 285Model-BasedReviewed 2024
Model-Based RL: Learning the Model CS 224RCS 285Model-BasedReviewed 2024
Model-Based RL: Improving PoliciesCS 224RCS 285Model-BasedReviewed 2024
BanditsCS 234ExplorationReviewed 2024
MDP ExplorationCS 234Exploration
Deep ExplorationCS 285ExplorationReviewed 2024
Exploration without RewardsCS 285ExplorationReviewed 2024
Offline Reinforcement Learning CS 224RCS 285Reviewed 2024
Control as InferenceCS 285Reviewed 2024
Reward Learning (overview)CS 224R
Inverse Reinforcement LearningCS 234CS 285Reviewed 2024
Multi-Task LearningCS 224RExtra
Coordinated ExplorationCS 234ExplorationExtra
Deep RL on Real RobotsCS 224R
Meta-RLCS 224R
Reset-Free RLCS 224R
Skill DiscoveryCS 224R