Machine-Learning-Tokyo / Deep_reinforcement_learning
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🤖 Implements of Reinforcement Learning algorithms.
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Deep Reinforcement Learning
Introduction to Reinforcement Learning with David Silver, DeepMind
Watch the lectures from DeepMind research lead David Silver's course on reinforcement learning, taught at University College London.
- Lecture 1: Introduction 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
Deep Reinforcement Learning: A Brief Survey
Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage, Anil Anthony Bharath
Spinning Up in Deep RL
Educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). It includes the following resources:
- a short introduction to RL terminology, kinds of algorithms, and basic theory,
- an essay about how to grow into an RL research role,
- a curated list of important papers organized by topic,
- a well-documented code repo of short, standalone implementations of key algorithms,
- and a few exercises to serve as warm-ups.
Stanford CS234: Reinforcement Learning
Lecture Series. Stanford CS234: Reinforcement Learning (Winter 2019) - with Prof. Emma Brunskill
An Introduction to Deep Reinforcement Learning (2018)
Vincent Francois-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau
[PDF Book manuscript, Nov 2018]
CS294-112 Deep Reinforcement Learning
Lecture Series. UC Berkeley. Fall 2018.
Instructor : Sergey Levine
CS885 Reinforcement Learning
Lecture Series. University of Waterloo. Spring 2018
Instructor: Pascal Poupart
Advanced Deep Learning & Reinforcement Learning
Deepmind 2018.
RLSS 2018
Toronto 2018.
RLSS 2017
Montreal 2017.
Deep RL Bootcamp
Berkeley CA. Aug 2017
Introduction to Reinforcement Learning
DeepMind, 2015
Instructor : David Silver
Deep RL Bootcamp, Berkeley (2017)
By Pieter Abbeel, Chelsea Finn, Peter Chen, Andrej Karpathy et al.
Reinforcement Learning Book
Written by Richard Sutton and Andrew Barto.
Denny Britz: Reinforcement Learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course. All code is written in Python 3 and uses RL environments from OpenAI Gym. Advanced techniques use Tensorflow for neural network implementations.
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