Showing 4 open source projects for "8-puzzle reinforcement learning python"

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  • 1
    NVIDIA Isaac Lab

    NVIDIA Isaac Lab

    Unified framework for robot learning built on NVIDIA Isaac Sim

    Isaac Lab is an open-source modular robotics learning framework built atop Isaac Sim. It simplifies research workflows across reinforcement learning, imitation learning, and motion planning by offering robust, GPU-accelerated simulation with realistic sensor and physics fidelity—ideal for sim-to-real robot training. Compatible and optimized for use with Isaac Sim versions (e.g., Sim 5.0 and 4.5). GPU-accelerated, high-fidelity physics and sensor simulation suitable for complex learning...
    Downloads: 6 This Week
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  • 2
    Open X-Embodiment

    Open X-Embodiment

    Unified open dataset enabling cross-embodiment learning for robotics

    Open X-Embodiment is a large-scale collaborative initiative led by Google DeepMind to unify robotic learning datasets into a consistent and standardized format, simplifying access and usage across the robotics research community. Its primary goal is to make all available open-source robotic data interoperable by representing them using the RLDS (Reinforcement Learning Dataset Structure) episode format. This enables seamless integration for training, evaluation, and model development across...
    Downloads: 0 This Week
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  • 3
    RoboSchool

    RoboSchool

    Open source software for robot simulation, integrated with OpenAI Gym

    Roboschool is a set of open source robot simulation environments for reinforcement learning, created as an alternative to the Mujoco physics engine. It integrates with OpenAI Gym and provides a variety of continuous control tasks, including humanoid locomotion, quadrupeds, and robotic arms. The library is built on the Bullet Physics engine, making it accessible without the licensing requirements of Mujoco. Roboschool includes training scripts and examples for applying reinforcement learning...
    Downloads: 2 This Week
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  • 4
    General purpose agents using reinforcement learning. Combines radial basis functions, temporal difference learning, planning, uncertainty estimations, and curiosity. Intended to be an out-of-the-box solution for roboticists and game developers.
    Downloads: 0 This Week
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