Showing 9 open source projects for "python q learning"

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  • 1
    AgentUniverse

    AgentUniverse

    agentUniverse is a LLM multi-agent framework

    AgentUniverse is a multi-agent AI framework that enables coordination between multiple intelligent agents for complex task execution and automation.
    Downloads: 0 This Week
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  • 2
    VectorizedMultiAgentSimulator (VMAS)

    VectorizedMultiAgentSimulator (VMAS)

    VMAS is a vectorized differentiable simulator

    VectorizedMultiAgentSimulator is a high-performance, vectorized simulator for multi-agent systems, focusing on large-scale agent interactions in shared environments. It is designed for research in multi-agent reinforcement learning, robotics, and autonomous systems where thousands of agents need to be simulated efficiently.
    Downloads: 0 This Week
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  • 3
    PilottAI

    PilottAI

    Python framework for building scalable multi-agent systems

    pilottai is an AI-based autonomous drone navigation system utilizing reinforcement learning for real-time decision-making. It is designed for simulating and training drones to fly safely through dynamic environments using AI-based controllers.
    Downloads: 0 This Week
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  • 4
    LiteMultiAgent

    LiteMultiAgent

    The Library for LLM-based multi-agent applications

    LiteMultiAgent is a lightweight and extensible multi-agent reinforcement learning (MARL) platform designed for rapid experimentation. It allows researchers to design and test coordination, competition, and collaboration scenarios in simulated environments.
    Downloads: 0 This Week
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  • 5
    AgentForge

    AgentForge

    Extensible AGI Framework

    AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications.
    Downloads: 1 This Week
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  • 6
    OpenAI Swarm

    OpenAI Swarm

    Educational framework exploring multi-agent orchestration

    Swarm focuses on making agent coordination and execution lightweight, highly controllable, and easily testable. It accomplishes this through two primitive abstractions; Agents and handoffs. An Agent encompasses instructions and tools, and can at any point choose to hand off a conversation to another Agent. These primitives are powerful enough to express rich dynamics between tools and networks of agents, allowing you to build scalable, real-world solutions while avoiding a steep learning...
    Downloads: 2 This Week
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  • 7
    Zeta

    Zeta

    Build high-performance AI models with modular building blocks

    zeta is a deep learning library focused on providing cutting-edge AI and neural network models with a strong emphasis on research-grade architectures. It includes state-of-the-art implementations for rapid experimentation and model building.
    Downloads: 0 This Week
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  • 8
    OWL

    OWL

    Optimized Workforce Learning for General Multi-Agent Assistance

    Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation. OWL (Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation) is an advanced framework designed to enhance multi-agent collaboration, improving task automation across various domains. By utilizing dynamic agent interactions, OWL aims to streamline and optimize complex workflows, making AI collaboration more natural, efficient, and adaptable. It is built on...
    Downloads: 0 This Week
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  • 9
    XAgent

    XAgent

    An Autonomous LLM Agent for Complex Task Solving

    XAgent is an AI-driven autonomous agent framework capable of handling multi-step tasks across different domains. It enables AI agents to perform decision-making, task planning, and self-learning based on user-defined objectives, making it ideal for automation and research applications.
    Downloads: 0 This Week
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