AI for Prosthetics
This is a guide for the NIPS 2018 AI for Prosthetics challenge with a helper package and a series of blog posts.
Read about state-of-the-art results for each environment of Atari 2600, the standard suite for analyzing performance of various Reinforcement Learning methods.
Read about continuous control environments created with MuJoCo, a proprietary physics engine for detailed, efficient rigid body simulations with contacts.
CTRL: Current Topics in RL
Read summaries of new papers in Reinforcement Learning, ranging from theoretical studies to experiments.
Read the early draft of the Deep Q-Networks (DQN) book. This book explores various improvements of DQN that achieved superhuman results.
Sutton and Barto Notebooks
This repository contains Jupyter Notebook of implementations of insightful figures in Sutton and Barto's Reinforcement Learning: An Introduction.
This is a collection of presentation slides summarizing contents of books and state-of-the-art results.