A Scalable Communication Protocol for Networks of Large Language Models
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866909351177879552 |
|---|---|
| author | Marro, Samuele La Malfa, Emanuele Wright, Jesse Li, Guohao Shadbolt, Nigel Wooldridge, Michael Torr, Philip |
| author_facet | Marro, Samuele La Malfa, Emanuele Wright, Jesse Li, Guohao Shadbolt, Nigel Wooldridge, Michael Torr, Philip |
| contents | Communication is a prerequisite for collaboration. When scaling networks of AI-powered agents, communication must be versatile, efficient, and portable. These requisites, which we refer to as the Agent Communication Trilemma, are hard to achieve in large networks of agents. We introduce Agora, a meta protocol that leverages existing communication standards to make LLM-powered agents solve complex problems efficiently. In Agora, agents typically use standardised routines for frequent communications, natural language for rare communications, and LLM-written routines for everything in between. Agora sidesteps the Agent Communication Trilemma and robustly handles changes in interfaces and members, allowing unprecedented scalability with full decentralisation and minimal involvement of human beings. On large Agora networks, we observe the emergence of self-organising, fully automated protocols that achieve complex goals without human intervention. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_11905 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Scalable Communication Protocol for Networks of Large Language Models Marro, Samuele La Malfa, Emanuele Wright, Jesse Li, Guohao Shadbolt, Nigel Wooldridge, Michael Torr, Philip Artificial Intelligence Machine Learning I.2.11; I.2.7 Communication is a prerequisite for collaboration. When scaling networks of AI-powered agents, communication must be versatile, efficient, and portable. These requisites, which we refer to as the Agent Communication Trilemma, are hard to achieve in large networks of agents. We introduce Agora, a meta protocol that leverages existing communication standards to make LLM-powered agents solve complex problems efficiently. In Agora, agents typically use standardised routines for frequent communications, natural language for rare communications, and LLM-written routines for everything in between. Agora sidesteps the Agent Communication Trilemma and robustly handles changes in interfaces and members, allowing unprecedented scalability with full decentralisation and minimal involvement of human beings. On large Agora networks, we observe the emergence of self-organising, fully automated protocols that achieve complex goals without human intervention. |
| title | A Scalable Communication Protocol for Networks of Large Language Models |
| topic | Artificial Intelligence Machine Learning I.2.11; I.2.7 |
| url | https://arxiv.org/abs/2410.11905 |