Pre-requisites

<aside> <img src="https://noticon-static.tammolo.com/dgggcrkxq/image/upload/v1586271210/noticon/sageach1qrmmyfufwli1.gif" alt="https://noticon-static.tammolo.com/dgggcrkxq/image/upload/v1586271210/noticon/sageach1qrmmyfufwli1.gif" width="40px" /> David Silver 강의 내용 정리 (link)

Lecture 1: Introdunction to Reinforcement Learning

Lecture 2: Markov Decision Processes

Lecture 3: Planning by Dynamic Programming

Lecture 4: Model-Free Prediction

Lecture 5: Model-Free Control

Lecture 6: Value Function Approximation

Lecture 7: Policy Gradient Methods

Lecture 8: Integrating Learning and Planning

Lecture 9: Exploration and Exploitation

Lecture 10: Case Study: RL in Classic Games

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<aside> 🗞️ Key Papers in Deep RL (link)

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Categories

Decision Transformer

Multi-agent Reinforcement Learning