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Table of contents

RL Diagram

Optimal Control ๐ŸŽฏ

Dynamic Programming

Tree-Based Planning

Control Theory

Model Predictive Control

Safe Control ๐Ÿ”’

Robust Control

Risk-Averse Control

Value-Constrained Control

State-Constrained Control and Stability

Uncertain Dynamical Systems

Game Theory โ™ ๏ธ

Sequential Learning ๐Ÿ‘ž

Multi-Armed Bandit ๐ŸŽฐ

Best Arm Identification ๐Ÿ’ช

Black-box Optimization โฌ›๏ธ

Reinforcement Learning ๐Ÿค–

Theory ๐Ÿ“š

Generative Model

Policy Gradient

Linear Systems

Value-based ๐Ÿ“ˆ

Policy-based ๐Ÿ’ช

Policy gradient

Actor-critic

Derivative-free

Model-based ๐Ÿ—บ

Exploration โ›บ๏ธ

Hierarchy and Temporal Abstraction ๐Ÿ•‘

Partial Observability ๐Ÿ‘

Transfer ๐ŸŒŽ

Multi-agent ๐Ÿ‘ฌ

Representation Learning

Other

Learning from Demonstrations ๐ŸŽ“

Imitation Learning

Applications to Autonomous Driving ๐Ÿš—

Inverse Reinforcement Learning

Applications to Autonomous Driving ๐Ÿš•

Motion Planning ๐Ÿƒ

Search

Sampling

Optimization

Reactive

Architecture and applications


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