[agents] Rethinking Multi-Agent Systems in the Era of LLMs / Workshop / 16 Sept 2025 / University of Oxford

Michael Wooldridge michael.john.wooldridge at gmail.com
Wed Jul 23 11:01:55 EDT 2025


Rethinking Multi-agent Systems in the Era of LLMs

A One-Day Workshop - University of Oxford, UK

* Call for Expressions of Interest *

16 September 2025

https://sites.google.com/view/rethinking-mas/home


OVERVIEW

The field of multi-agent systems emerged in the early 1990s, driven by
the vision that the future of AI would involve networks of AI programs
- agents - operating autonomously in pursuit of user-delegated
goals. A crucial part of this vision was that these agents would need
to interact with one-another in pursuit of their delegated goals,
which led to much work in the development of agents with social
skills: the ability to cooperate, coordinate, and negotiate.

The emergence of Large-Language Models (LLMs) has led to massive
renewed interest in multi-agent systems. Most LLMs are fundamentally
chatbots: they aren't equipped with the ability to carry out actions,
or to interact with other AI systems. There is much interest currently
in the possibility of LLM-powered agents, which leverage the general
intelligence of LLMs in systems that can act autonomously, exactly as
was envisaged in the original dream of multi-agent systems. In
addition, there is evidence that structuring a system as a collection
of interacting agents, each playing a specific role, can be a useful
way to build complex problem solving systems.

This workshop aims to bring together those interested in LLM-based
multi-agent systems. The goals of the event are, firstly, to try to
understand how the new technology of LLMs can be best used to realise
the classic vision of multi-agent systems, and second, what can be
learned from classic multi-agent systems in the LLM-agent era.


TOPICS OF INTEREST

Include but are not restricted to...

Revisiting classic multi-agent architectures in light of LLM capabilities
             Architectures for LLM agents
            LLMs as agents vs. tools
            Emergent behaviours in LLM-powered agent societies
            Standards for LLM agents: MCP, A2A, ...

Communication and Coordination
   Language as the primary protocol - agents communicating via
              natural language vs. symbolic messages
            Grounding meaning and shared understanding among LLM agents
            Ontologies for LLM-powered agents

Negotiation, persuasion, and argumentation with LLM agents
            Trust, deception, and misinformation in LLM-based agent societies
            Emergence of shared mental models/collective intelligence
            Dialogue protocols and structured conversations for LLM MAS

Learning and Adaptation
            On-the-fly role learning and specialization among LLM agents
            Multi-agent reinforcement learning with language-based policies
            Meta-learning in agent collectives using LLMs

Evaluation and Benchmarking
            Benchmarks for multi-agent communication involving LLMs
            Token-efficient dialogues
            Emergent cooperation / competition / collusion
            Robustness and safety of LLM-powered agent collectives

Ethics, Safety, and Governance
            Detecting and mitigating unintended/emergent behaviours
            Alignment of multi-agent objectives when agents have LLM-driven autonomy
            Social biases and value alignment in agent interactions
            Regulatory and societal implications of scalable LLM-based agent swarms

 Applications and Case Studies
            Collaborative problem solving (e.g., scientific discovery, design)
            Multi-agent simulations for economic or policy modeling
            Large-scale digital societies and synthetic populations
            Human-agent teams: hybrid collaboration settings
            Multi-agent gaming and open-ended virtual worlds

Game theory and LLM-based multi-agent systems
   Mechanism design for LLM-agent protocols
            LLM agents as rational actors
            Convergence to game theoretic solutions

Future Directions
            Bridging symbolic and sub-symbolic reasoning in agent collectives
            Designing societal-level intelligence: beyond individual agent optimization
            LLM-based robotic AI


HOW TO PARTICIPATE

We are seeking expressions of interest for participation by giving a
talk or demo. Please submit your expression of interest via EasyChair:

    https://easychair.org/conferences?conf=rethinkmas2025

Note we do *NOT* require original unpublished research, or indeed the
submission of technical papers. We are looking for expressions of
interest to present research or demos, and the submission process is
lightweight.

During the submission, you will be asked to upload a paper: you can
upload a paper (published or unpublished), report, presentation, or
any other document in the form of a PDF, to support your
application.

You should use the abstract to briefly describe what work you want to
present and how it relates to the theme of the event.

  * DEADLINE FOR EXPRESSIONS OF INTEREST: FRIDAY 8 AUGUST 2025 AOE *

Expressions of interest will be only lightly reviewed, focussing on
relevance/interest. Detailed reviews will not be provided. A token fee
will be charged for attendance; consideration will be given for
participants unable to pay the fee.


WHEN AND WHERE

The workshop will be a 1-day event held on 16 Sept 2025 at:

            Department of Computer Science
            University of Oxford
            Oxford
            OX1 3QD
            United Kingdom


ORGANISATION

* Michael Wooldridge [University of Oxford] mjw at cs.ox.ac.uk<mailto:mjw at cs.ox.ac.uk> *Main Contact*
* Sarit Kraus [Bar Ilan University, Israel]
* Emanuele la Malfa [University of Oxford]
* Samuele Marro [University of Oxford]


SUPPORT

This event is supported by the Schmidt Sciences Foundation under an
AI2020 Senior Fellowship awarded to Michael Wooldridge, and by the
UKRI under the AI Hub on Generative AI (https://www.genai.ac.uk).

--
Michael Wooldridge
Ashall Professor of the Foundations of Artificial Intelligence, University of Oxford

PA: Jenny Dollard <jenny.dollard at cs.ox.ac.uk<mailto:jenny.dollard at cs.ox.ac.uk>>


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