Sacha Chernyavskiy's repositories
UnityPeekaboo
Unity ML-Agents based multi-agent environment for goal conditioned tasks
alexunderch.github.io
A beautiful, simple, clean, and responsive Jekyll theme for academics
Awesome-Evolutionary-Reinforcement-Learning
Research Papers and Code Repository on the Integration of Evolutionary Algorithms and Reinforcement Learning
cfrx
cfrx is a collection of algorithms and tools for hardware-accelerated Counterfactual Regret Minimization (CFR) algorithms in Jax.
deep-rl-class
This repo contain the syllabus of the Hugging Face Deep Reinforcement Learning Class.
diffusion-models-class
Materials for the Hugging Face Diffusion Models Course
DiffusionModelsTryOut
Some ablations on diffusion models to better understand their principles
dreamerv2
Pytorch implementation of Dreamer-v2: Visual Model Based RL Algorithm.
JaxMARL
Multi-Agent Reinforcement Learning with JAX
mamba
This code accompanies the paper "Scalable Multi-Agent Model-Based Reinforcement Learning".
mcts-for-kids
A mcts-based modular lib to maintain some projects
minimax
Efficient baselines for autocurricula in JAX.
mjctrl
Single-file pedagogical implementations of robotics controllers for MuJoCo.
ml-agents-patch
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
pax
Scalable Opponent Shaping Experiments in JAX
pogema
POGEMA stands for Partially-Observable Grid Environment for Multiple Agents. This is a grid-based environment that was specifically designed to be flexible, tunable and scalable. It can be tailored to a variety of PO-MAPF settings.
PufferLib
Simplifying reinforcement learning for complex game environments
ReMiDi
Code for the paper Refining Minimax Regret for Unsupervised Environment Design (ICML 2024) https://arxiv.org/abs/2402.12284
serl
SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning
xland-minigrid
JAX-accelerated Meta-Reinforcement Learning Environments Inspired by XLand and MiniGrid 🏎️