This repository serves as a curated survey of research papers focused on Large Language Model (LLM)-based Multi-Agent systems. It categorizes and lists papers across five key streams: Frameworks, Orchestration/Efficiency, Problem Solving, World Simulation, and Datasets/Benchmarks, aiming to provide a comprehensive overview for researchers and practitioners in the field.

How It Works

The project compiles and categorizes academic papers related to LLM-based multi-agent systems. It organizes these papers into distinct research areas, facilitating a structured understanding of the field's progress and challenges. The survey aims to cover a broad spectrum of applications, from software development and scientific experiments to social simulations and game theory.

Quick Start & Requirements

This repository is a collection of research papers and does not have a direct installation or execution command. The primary resource is the survey paper itself, available at: https://arxiv.org/abs/2402.01680.

Highlighted Details

• Comprehensive categorization of LLM-based multi-agent research into five main streams.
• Extensive list of papers with links, covering frameworks, orchestration, problem-solving, world simulation, and benchmarks.
• Regular updates to include newly published relevant papers.
• Focus on diverse applications including software development, embodied agents, scientific operations, and social simulations.

Maintenance & Community

The repository is maintained by Taicheng Guo (tguo2@nd.edu, Twitter: https://twitter.com/taioooorange). Contributions are welcomed via pull requests or issues to ensure the list remains up-to-date.

Licensing & Compatibility

The licensing information for the repository itself is not explicitly stated in the README. The linked papers are subject to their respective publication licenses.

Limitations & Caveats

The repository is a survey and does not provide executable code or frameworks. The accuracy and completeness of the paper list depend on community contributions and the curator's ongoing efforts.