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openai/mujoco-py

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0 stele·0 fork-uri·7 vizualizări

Mujoco Py

MuJoCo is a physics engine which can do very detailed efficient simulations with contacts. This library lets you use MuJoCo from Python.

Features

  • Model-Based Reinforcement Learning - Physics-based simulation environment for continuous control and robotics research.
  • Reinforcement Learning Environments - Python bindings for high-performance physics simulation in robotics and control.
  • World Models - Physics engine interface for high-fidelity robotic and control simulations.
  • Environment Benchmarks - Enables physics-based simulation for reinforcement learning research.

Istoric stele

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Alternative open-source pentru Mujoco Py

Proiecte open-source similare, clasificate după numărul de funcționalități comune cu Mujoco Py.
  • rail-berkeley/d4rlAvatar rail-berkeley

    rail-berkeley/d4rl

    1,693Vezi pe GitHub↗

    D4RL is an open-source benchmark for offline reinforcement learning. It provides standardized environments and datasets for training and benchmarking algorithms. A supplementary whitepaper and website are also available.

    Python
    Vezi pe GitHub↗1,693
  • openai/gymAvatar openai

    openai/gym

    37,223Vezi pe GitHub↗

    Gym is a reinforcement learning environment toolkit and agent simulation framework. It provides a standardized API and a universal communication interface that defines how learning agents interact with simulation environments through actions and observations. The project includes a benchmark environment suite and a diverse library of pre-configured simulation worlds, including physics engines and classic control tasks. It enables the creation of custom simulation environments to train agents in specific operational scenarios while ensuring reproducibility across different learning algorithms.

    Python
    Vezi pe GitHub↗37,223
  • aravindr93/mjrlA

    aravindr93/mjrl

    0Vezi pe GitHub↗

    This package contains implementations of various RL algorithms for continuous control tasks simulated with MuJoCo.

    Vezi pe GitHub↗0
  • danijar/crafterAvatar danijar

    danijar/crafter

    566Vezi pe GitHub↗

    Status: Stable release

    Python
    Vezi pe GitHub↗566
Vezi toate cele 30 alternative pentru Mujoco Py→

Întrebări frecvente

Ce face openai/mujoco-py?

MuJoCo is a physics engine which can do very detailed efficient simulations with contacts. This library lets you use MuJoCo from Python.

Care sunt principalele funcționalități ale openai/mujoco-py?

Principalele funcționalități ale openai/mujoco-py sunt: Model-Based Reinforcement Learning, Reinforcement Learning Environments, World Models, Environment Benchmarks.

Care sunt câteva alternative open-source pentru openai/mujoco-py?

Alternativele open-source pentru openai/mujoco-py includ: rail-berkeley/d4rl — D4RL is an open-source benchmark for offline reinforcement learning. It provides standardized environments and… openai/gym — Gym is a reinforcement learning environment toolkit and agent simulation framework. It provides a standardized API and… maximecb/gym-minigrid — Simple and easily configurable grid world environments for reinforcement learning. deepmind/lab — Lab is a customizable 3D platform and research testbed designed for training and testing autonomous agents using… aravindr93/mjrl — This package contains implementations of various RL algorithms for continuous control tasks simulated with MuJoCo. danijar/crafter — Status: Stable release.