https://github.com/Farama-Foundation/Metaworld

Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning
https://github.com/Farama-Foundation/Metaworld

benchmark-environments meta-rl mujoco multi-task

Last synced: 28 days ago
JSON representation

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

• Host: GitHub
• URL: https://github.com/Farama-Foundation/Metaworld
• Owner: Farama-Foundation
• License: mit
• Created: 2019-09-09T19:00:02.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2024-08-18T08:55:50.000Z (8 months ago)
• Last Synced: 2024-10-29T15:34:47.073Z (6 months ago)
• Topics: benchmark-environments, meta-rl, mujoco, multi-task
• Language: Python
• Homepage: https://metaworld.farama.org/
• Size: 91.6 MB
• Stars: 1,262
• Watchers: 29
• Forks: 271
• Open Issues: 19
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-real-world-rl - RL Robotic Meta World - Robotic Manipulation Tasks - Real world examples regarding to Meta Learning. (Libraries)
• awesome-model-based-RL - Meta-World - py) (Papers / ICML 2023)
• awesome-decision-transformer - MetaWorld - deepmind/dm_control) (Papers / ICLR 2023)
• awesome-production-machine-learning - Meta-World - Foundation/Metaworld.svg?style=social) - Meta-World is an open-source simulated benchmark for meta-reinforcement learning and multi-task learning consisting of 50 distinct robotic manipulation tasks. (Evaluation and Monitoring)