LLM Multi-Agent Systems: Challenges and Open Problems

TL;DR

This paper reviews the challenges and open problems in multi-agent systems involving large language models, focusing on collaboration, reasoning, context management, and applications in blockchain.

Contribution

It identifies key unresolved issues in multi-agent systems with LLMs and discusses potential solutions and future research directions.

Findings

Highlighting the importance of task allocation and reasoning

Addressing context and memory management challenges

Exploring applications in blockchain systems

Abstract

This paper explores multi-agent systems and identify challenges that remain inadequately addressed. By leveraging the diverse capabilities and roles of individual agents, multi-agent systems can tackle complex tasks through agent 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 potential applications of multi-agent systems in blockchain systems to shed light on their future development and application in real-world distributed systems.