Mastering Atari with Discrete World Models

Continual reinforcement learning baselines: experiment specifications, implementation of existing methods, and common metrics. Easily extensible to new methods.

A list of papers regarding generalization in (deep) reinforcement learning

📴 OffCon^3: SOTA PyTorch SAC and TD3 Implementations (arxiv: 2101.11331)

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyp…

Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning

🧠🗼

🔍 Codebase for the ICML '20 paper "Ready Policy One: World Building Through Active Learning" (arxiv: 2002.02693)

bsuite is a collection of carefully-designed experiments that investigate core capabilities of a reinforcement learning (RL) agent

🧶 Minimal PyTorch Soft Actor Critic (SAC) implementation

Deep Neuroevolution

Final project for big data and machine learning.

tutorial notebooks

Materials for the 2017 QMSS Python Workshop

This will serve as the public forum repository to which anyone can post. [Don't put your graded homework here!]