Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning

A Python package for job-shop modeling

Modular Reinforcement Learning (RL) library (implemented in PyTorch, JAX, and NVIDIA Warp) with support for Gymnasium/Gym, NVIDIA Isaac Lab, Brax and other environments

An object-oriented algebraic modeling language in Python for structured optimization problems.

Official implementation of paper "Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning"

JMLR: OmniSafe is an infrastructural framework for accelerating SafeRL research.

Environments for OR and RL Research

SafeRL Environments Implementations

Next-generation scheduling problem solver based on GNNs and Reinforcement Learning

Simulation and reinforcement learning framework for production planning and control of complex job shop manufacturing systems

Computational framework for reinforcement learning in traffic control

🦀 Small exercises to get you used to reading and writing Rust code!

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKT…

This is the official implementation of Multi-Agent PPO (MAPPO).

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

The best ChatGPT that $100 can buy.

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

BenchMARL is a library for benchmarking Multi-Agent Reinforcement Learning (MARL). BenchMARL allows to quickly compare different MARL algorithms, tasks, and models while being systematically ground…

Implementation of 'RL^2: Fast Reinforcement Learning via Slow Reinforcement Learning'

Platform for designing and evaluating Graph Neural Networks (GNN)

Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen2.5, Qwen3, Llama, and more!

Kolmogorov Arnold Networks

An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities

Your first pick for a django power cord

Reinforcement Learning environments for Traffic Signal Control with SUMO. Compatible with Gymnasium, PettingZoo, and popular RL libraries.

Reinforcement learning approach for job shop scheduling