Multi-agent Systems in the Era of LLMs: Progress and Prospects


The original metaphor for the field of multi-agent systems was that of a team of experts, each with distinct expertise, cooperating to solve a problem that was beyond the capabilities of any individual expert. “Cooperative distributed problem solving”, as it was originally called, eventually broadened to consider all issues that arise when multiple AI systems interact. The emergence and dramatic success of Large Language Models (LLMs) has given new life to the old dream. A raft of LLM-powered agent frameworks have become available, and multi-agent LLMs are increasingly being adopted. In this talk, we’ll survey the main approaches, opportunities, and outstanding challenges for multi-agent systems in new world of LLM-based AI.


Michael Wooldridge is a Professor of Computer Science at the University of Oxford. He has been an AI researcher for more than 30 years, and has published more than 400 scientific articles on the subject, including nine books. He is a Fellow of the Association for Computing Machinery (ACM), the Association for the Advancement of AI (AAAI), and the European Association for AI (EurAI). From 2014-16, he was President of the European Association for AI, and from 2015-17 he was President of the International Joint Conference on AI (IJCAI).

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