Computer Science > Multiagent Systems
arXiv:2402.03578 (cs)
[Submitted on 5 Feb 2024]
Title:LLM Multi-Agent Systems: Challenges and Open Problems
View a PDF of the paper titled LLM Multi-Agent Systems: Challenges and Open Problems, by Shanshan Han and 5 other authors
View PDFHTML (experimental)Abstract:This paper explores existing works of multi-agent systems and identifies challenges that remain inadequately addressed. By leveraging the diverse capabilities and roles of individual agents within a multi-agent system, these systems can tackle complex tasks through collaboration. We discuss optimizing task allocation, fostering robust reasoning through iterative debates, managing complex and layered context information, and enhancing memory management to support the intricate interactions within multi-agent systems. We also explore the potential application of multi-agent systems in blockchain systems to shed light on their future development and application in real-world distributed systems.
| Subjects: | Multiagent Systems (cs.MA); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2402.03578 [cs.MA] |
| (orarXiv:2402.03578v1 [cs.MA] for this version) | |
| https://doi.org/10.48550/arXiv.2402.03578 arXiv-issued DOI via DataCite |
Full-text links:
Access Paper:
- View PDF
- HTML (experimental)
- TeX Source
- Other Formats
View a PDF of the paper titled LLM Multi-Agent Systems: Challenges and Open Problems, by Shanshan Han and 5 other authors
References & Citations
Bookmark
Bibliographic and Citation Tools
Bibliographic Explorer(What is the Explorer?)
Connected Papers(What is Connected Papers?)
Litmaps(What is Litmaps?)
scite Smart Citations(What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv(What is alphaXiv?)
CatalyzeX Code Finder for Papers(What is CatalyzeX?)
DagsHub(What is DagsHub?)
Gotit.pub(What is GotitPub?)
Hugging Face(What is Huggingface?)
Papers with Code(What is Papers with Code?)
ScienceCast(What is ScienceCast?)
Demos
Recommenders and Search Tools
Influence Flower(What are Influence Flowers?)
CORE Recommender(What is CORE?)
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community?Learn more about arXivLabs.