Multi-Agent Systems for Mac

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  • 1
    Langroid

    Langroid

    Harness LLMs with Multi-Agent Programming

    Given the remarkable abilities of recent Large Language Models (LLMs), there is an unprecedented opportunity to build intelligent applications powered by this transformative technology. The top question for any enterprise is: how best to harness the power of LLMs for complex applications? For technical and practical reasons, building LLM-powered applications is not as simple as throwing a task at an LLM system and expecting it to do it. Effectively leveraging LLMs at scale requires a principled programming framework. In particular, there is often a need to maintain multiple LLM conversations, each instructed in different ways, and "responsible" for different aspects of a task.
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  • 2
    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.
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  • 3

    MASLua

    Multi-agent system modeling with Lua

    A framework to simulate systems of agents in Lua on a 2D grid map, with modules for describing agent behavior and communication. A working example of a taxi fleet is given. The "basic" version uses conventional belief-desire-intention module (BDI.lua) for agent programming and a textual I/O. The "basic_EFSSM" version uses only state-oriented programming for agents. (Available soon.) --- Ribas-Xirgo, Ll.: Multi-agent system model of taxi fleets. In Advances in Physical Agents II, Springer International Publishing, 2021. Proceedings of the 21st International Workshop of Physical Agents (WAF 2020), November 19-20, 2020, Alcalá de Henares, Madrid, Spain.
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  • 4
    MASyV (Multi-Agent System Visualization) enables one to write agent-based models/cellular automata, eg. in C, visualize them in real time & capture to movie file with MASyVs GUI & message passing lib. Includes examples: Hello World, ants, viral infection
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  • 5
    MCMAS-C is an extension to the most famous model checker MCMAS, which is implemented to verify multi-agent system. Our extension is related to check social commitments that agents can create and their fulfillment. It is model checker for CTLC logic.
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  • 6
    MindSearch

    MindSearch

    An LLM-based Multi-agent Framework of Web Search Engine

    MindSearch is an AI-powered search engine based on large language models (LLMs) designed for deep semantic search and retrieval. It leverages InternLM's language model to understand complex queries and retrieve highly relevant answers from large datasets.
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  • 7
    Multi-Agent path planning in Python

    Multi-Agent path planning in Python

    Python implementation of a bunch of multi-robot path-planning

    multi_agent_path_planning is a Python-based implementation of multi-agent pathfinding algorithms for coordinating multiple agents in shared environments without collisions. It is useful in robotics, warehouse automation, and gaming AI.
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  • 8
    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.
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  • 9
    PraisonAI

    PraisonAI

    PraisonAI application combines AutoGen and CrewAI or similar framework

    PraisonAI application combines AutoGen and CrewAI or similar frameworks into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customization, and efficient human-agent collaboration. Chat with your ENTIRE Codebase. Praison AI, leveraging both AutoGen and CrewAI or any other agent framework, represents a low-code, centralized framework designed to simplify the creation and orchestration of multi-agent systems for various LLM applications, emphasizing ease of use, customization, and human-agent interaction.
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  • 10
    RWARE

    RWARE

    MuA multi-agent reinforcement learning environment

    robotic-warehouse is a simulation environment and framework for robotic warehouse automation, enabling research and development of AI and robotic agents to manage warehouse logistics, such as item picking and transport.
    Downloads: 0 This Week
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  • 11

    SpiLLI

    Decentralized AI Inference

    SpiLLI provides infrastructure to manage, host, deploy and run Decentralized AI inference
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  • 12
    This project simulates a multi-agent system (swarm) behavior both graphically and not. The purpose of this project is to research the properties suggested in "stability analysis of swarms" V.Gazi & K.M.Passino. Using the vpython library for 3D modeling
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  • 13
    SwarmZero

    SwarmZero

    SwarmZero's SDK for building AI agents, swarms of agents and much more

    SwarmZero is an open-source platform designed for deploying and managing autonomous robot swarms. It enables collective coordination, decentralized decision-making, and real-time collaboration among large groups of autonomous agents, focusing on multi-robot systems and research in swarm robotics.
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  • 14
    Using agent technology JAMAS (Java Awareness Multi-Agent System) tries to assist distributed programmers in coordinating parallel development of Java code. E-JAMAS implements JAMAS and it’s features as a plug-in for the Eclipse platform.
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  • 15
    The Virtual Storyteller is a multi-agent framework for generating stories based on a concept called emergent narrative.
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  • 16
    Urban is a software capable of procedurally creating 3d urban environments. It's based on a multi-agent system where each agent is responsible for one type of urban object. This means the system is highly modular and can easily be extended.
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  • 17
    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.
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  • 18
    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.
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  • 19

    dnrDALMAS

    A general-level Prolog implementation of the DALMAS architecture.

    DnrDALMAS is a Prolog module intended to be a general-level Prolog implementation of the abstract DALMAS (Deontic Action-Logic based Multi-Agent System) architecture. A DALMAS is regulated by a normative system based on an algebraic version of the theory of normative positions. For more information about dnrDALMAS, see the following technical report: Hjelmblom, M. (2008). Deontic action-logic multi-agent systems in Prolog. University of Gävle, Division of Computer Science; University of Gävle. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-1475 See also: Odelstad, J., & Boman, M. (2004). Algebras for Agent Norm-Regulation. Annals of Mathematics and Artificial Intelligence, 42(1), 141–166. http://doi.org/10.1023/B:AMAI.0000034525.49481.4a
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  • 20
    Meme is a multi-agent system. It aggregates literature information gathered from different sources into a viable format. It provides a visualization search and exports the literature information for users. It also integrates JADE and Nutch.
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