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2023-05-11
A collection of resources relevant to the study of reinforcement learning.
An RL agent completes a 2D model moon landing in the lunar lander environment.
[1] These are considered the primary introductions to Reinforcement Learning:
2019 | "Reinforcement Learning: An Introduction" by Sutton & Barto
2015 | David Silver's UCL Lectures
[2] Pieter Abbeel’s 6-part lecture series is intuitively explained, giving each topic’s motivation:
[3] Bertsekas' book provides a comprehensive research focussed approach:
2023 | "A Course in Reinforcement Learning"
[4] Hugging Face provide a well structured & popular contemporary DeepRL course:
2018 | Welcome to the 🤗 Deep Reinforcement Learning Course
[5] Lillian Weng's blog post below is a superb reference for the core concepts:
Provides the standard interface for reinforcement learning environments, in addition to a collection of common environments.
Reliable PyTorch-based implementations of widely used RL algorithms.
[6] REINFORCEjs: Interactive DP, TD-learning & DQN in your browser!
An unmaintained (since 2022) but useful list of varying quality
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Feel free to send comments & corrections to me at:
Last updated 2023-05-17
