multi-agent-systems

🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX

Offical Implementation for "Recursive Multi-Agent Systems"

Autonomous AI pentesting engine across web, cloud, identity, CI/CD, IaC, databases, Active Directory, Kubernetes, IoT firmware and AI/LLM endpoints (OWASP LLM Top 10). Real exploits with proof for every finding. Privacy gateway: the LLM never sees your real IPs, hosts or creds; nothing leaves your perimeter.

Your AI agent in 30 seconds. Not 30 hours. Self-hosted, open-source personal AI with desktop installer, multi-agent Command Center(Deep Work), and 7-layer security. Anthropic, OpenAI, or Ollama.

Agent samples built using the Strands Agents SDK.

[ICRA 2022] An opensource framework for cooperative detection. Official implementation for OPV2V.

Self-healing infrastructure for AI agent payments. 90.3% auto-recovery.

More is Different. A multi-agent world engine where AI agents live, talk, compete, ally.

Sybil-resistant AI agent network with hardware-attested identity. Proof-of-Antiquity blockchain: physical machines across 15+ CPU architectures prove they are real silicon, not VM farms. Agent economy, micropayments, Solana bridge (wRTC). $0 VC.

AI Agent Orchestrator with Skills System - Give AI Agents superpowers: memory search, code graph queries, agent-to-agent messaging. Manage Claude, Codex or any AI Agent from one dashboard. Move Agents between computers and locations

灰狼优化算法(GWO)路径规划/轨迹规划/轨迹优化、多智能体/多无人机航迹规划

A no-code 3D playground to explore, design, and interact with Agentic AI systems

Multi-Agent + Automation: Workflows, Automation, Self-Improving Agents

Plan, Build, and Ship — with a team of AI agents instead of one

VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

AAAI 2024 Papers: Explore a comprehensive collection of innovative research papers presented at one of the premier artificial intelligence conferences. Seamlessly integrate code implementations for better understanding. ⭐ experience the forefront of progress in artificial intelligence with this repository!

RAI is a vendor agnostic agentic framework for Physical AI robotics, utilizing ROS 2 tools to perform complex actions, defined scenarios, free interface execution, log summaries, voice interaction and more.

GraphBit is the world’s first enterprise-grade Agentic AI framework, built on a Rust core with a Python wrapper for unmatched speed, security, and scalability. It enables reliable multi-agent workflows with minimal CPU and memory usage, making it production-ready for real-world enterprise environments.

🤖 Agentfy is a modular microservices architecture designed to process user requests and execute workflows across multiple social media platforms. ASK ONCE, LET THE AGENT DO THE REST!

A decentralized agent network for building collaborative, LLM-powered agent-to-agent (A2A) systems.

[ICLR 2026] A Framework for LLM-based Multi-Agent Reinforced Training and Inference

A Graph-Centric Framework for Orchestrating Multi-Agent Systems with Vibe Graphing.

Meta Agents Research Environments is a comprehensive platform designed to evaluate AI agents in dynamic, realistic scenarios. Unlike static benchmarks, this platform introduces evolving environments where agents must adapt their strategies as new information becomes available, mirroring real-world challenges.

The local-first operating system for building, running, and improving AI agents, workflows, and autonomous goals.

本项目为Generative Agents项目的重构+深度汉化版本，旨在为中文用户提供一个利于维护的基础版本，以便后续实验或功能拓展。

A MicroKernel Multi-Agents System Framework for Adaptive Social Simulation Powered by LLMs

The practical implementation of Aspire using Microservices, AI-Agents

Hands-on workshop: Build a multi-agent AI system from scratch — Deep Research Agent + Writing Workflow served as MCP servers. Includes code, slides, and video