Showing 9 open source projects for "decision"

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  • 1
    highway-env

    highway-env

    A minimalist environment for decision-making in autonomous driving

    HighwayEnv is an OpenAI Gym-compatible environment focused on autonomous driving scenarios. It provides flexible simulations for testing decision-making algorithms in highway, intersection, and merging traffic situations.
    Downloads: 0 This Week
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  • 2
    DI-engine

    DI-engine

    OpenDILab Decision AI Engine

    DI-engine is a unified reinforcement learning (RL) platform for reproducible and scalable RL research. It offers modular pipelines for various RL algorithms, with an emphasis on production-level training and evaluation.
    Downloads: 0 This Week
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  • 3
    TextWorld

    TextWorld

    ​TextWorld is a sandbox learning environment for the training

    ...Developed by Microsoft Research, TextWorld focuses on language understanding, planning, and interaction in complex, narrative-driven environments. It generates games procedurally, enabling scalable testing of agents’ natural language processing and decision-making abilities.
    Downloads: 0 This Week
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  • 4
    Reinforcement Learning Course Materials

    Reinforcement Learning Course Materials

    Lecture notes, tutorial tasks including solutions

    Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University. The source code for the entire course material is open and everyone is cordially invited to use it for self-learning (students) or to set up their own course (lecturers).
    Downloads: 0 This Week
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  • 5
    Agent S

    Agent S

    Agent S: an open agentic framework that uses computers like a human

    Agent S is an open-source agentic framework designed to enable autonomous computer use through an Agent-Computer Interface (ACI). Built to operate graphical user interfaces like a human, it allows AI agents to perceive screens, reason about tasks, and execute actions across macOS, Windows, and Linux systems. The latest version, Agent S3, surpasses human-level performance on the OSWorld benchmark, demonstrating state-of-the-art results in complex multi-step computer tasks. Agent S combines...
    Downloads: 4 This Week
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  • 6
    verl

    verl

    Volcano Engine Reinforcement Learning for LLMs

    VERL is a reinforcement-learning–oriented toolkit designed to train and align modern AI systems, from language models to decision-making agents. It brings together supervised fine-tuning, preference modeling, and online RL into one coherent training stack so teams can move from raw data to aligned policies with minimal glue code. The library focuses on scalability and efficiency, offering distributed training loops, mixed precision, and replay/buffering utilities that keep accelerators busy. ...
    Downloads: 0 This Week
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  • 7
    AI4U

    AI4U

    Multi-engine plugin to specify agents with reinforcement learning

    AI4U is a multi-engine plugin (Godot and Unity) that allows you to design Non-Player Characters (NPCs) of games using an agent abstraction. In addition, AI4U has a low-level API that allows you to connect the agent to any algorithm made available in Python by the reinforcement learning community specifically and by the Artificial Intelligence community in general. Reinforcement learning promises to overcome traditional navigation mesh mechanisms in games and to provide more autonomous...
    Downloads: 0 This Week
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  • 8
    TaskWeaver

    TaskWeaver

    A code-first agent framework for seamlessly planning analytics tasks

    TaskWeaver is a multi-agent AI framework designed for orchestrating autonomous agents that collaborate to complete complex tasks.
    Downloads: 0 This Week
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  • 9
    CCZero (中国象棋Zero)

    CCZero (中国象棋Zero)

    Implement AlphaZero/AlphaGo Zero methods on Chinese chess

    ChineseChess-AlphaZero is a project that implements the AlphaZero algorithm for the game of Chinese Chess (Xiangqi). It adapts DeepMind’s AlphaZero method—combining neural networks and Monte Carlo Tree Search (MCTS)—to learn and play Chinese Chess without prior human data. The system includes self-play, training, and evaluation pipelines tailored to Xiangqi's unique game mechanics.
    Downloads: 0 This Week
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