reinforcement-learning

This repository collects some codes that encapsulates commonly used algorithms in the field of machine learning. Most of them are based on Numpy, Pandas or Torch. You can deepen your understanding to related model and algorithm or revise it to get the customized code belongs yourself by referring to this repository.

A collection of multi agent environments based on OpenAI gym.

RLAnything (ICML 2026) & AutoTool (ICML 2026), DemyAgent: Open-Source RL for LLMs and Agentic Scenarios

API to run VirtualHome, a Multi-Agent Household Simulator

A unified framework for robot learning

Explore the Multimodal “Aha Moment” on 2B Model

Deploy walk-these-ways project on Unitree Go2

Published on Nature Machine Intelligence! The first real robot(quadrotor) based on differentiable physics training.

臺灣大學 (NTU) 李宏毅教授「機器學習 (Machine Learning) 2021 Spring 」課程筆記

[ICLR 2026] ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving

Related papers for reinforcement learning, including classic papers and latest papers in top conferences

Continual learning infra for self-improving agents

AAAI 2024 Papers: Explore a comprehensive collection of innovative research papers presented at one of the premier artificial intelligence conferences. Seamlessly integrate code implementations for better understanding. ⭐ experience the forefront of progress in artificial intelligence with this repository!

A curated list of papers on reinforcement learning for video generation

[ICML 2026] Official resources of "Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning".

An Asynchronous Reinforcement Learning Engine for Omni-Modal Post-Training at Scale

Benchmarking the Spectrum of Agent Capabilities

NeurIPS 2023: Safety-Gymnasium: A Unified Safe Reinforcement Learning Benchmark

Implementation of ChatGPT RLHF (Reinforcement Learning with Human Feedback) on any generation model in huggingface's transformer (blommz-176B/bloom/gpt/bart/T5/MetaICL)

Deep Reinforcement Learning (PPO) in Autonomous Driving (Carla) [from scratch]

Meta Agents Research Environments is a comprehensive platform designed to evaluate AI agents in dynamic, realistic scenarios. Unlike static benchmarks, this platform introduces evolving environments where agents must adapt their strategies as new information becomes available, mirroring real-world challenges.

A curated list of artificial intelligence resources (Courses, Tools, App, Open Source Project)

[NeurIPS 2025 Spotlight] LLM post-training suite — featuring ReasonFlux, ReasonFlux-PRM, and ReasonFlux-Coder.

MuJoCo fruit fly body model and locomotion RL tasks

UMI on Legs: Making Manipulation Policies Mobile with Manipulation-Centric Whole-body Controllers

Curated list of publicly accessible machine learning engineering courses from CalTech, Columbia, Berkeley, MIT, and Stanford.

Multi-Objective Reinforcement Learning algorithms implementations.

[CVPR 2025 Highlight] InterMimic: Towards Universal Whole-Body Control for Physics-Based Human-Object Interactions

A general-purpose, flexible, and easy-to-use simulator alongside an OpenAI Gym trading environment for MetaTrader 5 trading platform (Approved by OpenAI Gym)