Recent developments in foundation models have paved the way for the wide adoption of AI agents that interact with humans and each other. The cooperation and safety of those models are a necessity, especially as they gain autonomy and participate in high stakes markets as autonomous systems, making those markets agentic. However, those agentic markets face significant challenges as most existing methods at improving their performance and robustness presume critical use of policy and regulation, which are insufficient and too slow for an economy driven by a mixture of human and algorithmic participants, especially in zero-shot scenarios.
As we advance towards an AI-centric future, the emergence of markets, mechanisms, and mediation platforms dedicated to preference elicitation and resource allocation for those highly agentic systems is inevitable. We expect many existing multi-agent security and cooperation approaches to break in high-stakes situations where hyper-adversarial incentives are present. This is compounded by the emergence of complexity from AI interactions, exemplified by intricate interdependencies within agentic systems.
Given this complexity, how can we fully understand and assess the associated risks? How can we improve the performance and robustness of these markets? It is essential to draw lessons from traditional markets with less agentic AI (e.g., finance), to achieve robust incentives and economic security in a post-foundation model world. We recognize the need to incorporate principles of cryptography and robust market design. However, the sufficiency of these approaches is not certain. We aim to identify the missing elements and treat the study of market design in presence of agentic AI as a scientific discipline.
This workshop seeks to amalgamate insights from economics, mechanism design, game theory, and, crucially, real-world financial markets expertise for algorithmic agents to better prepare us for the inevitable mass adoption of agentic AI on mission critical jobs. We aspire for this workshop to enlighten participants about new agent-driven risks and opportunities, fostering disruptive collaborations among economists, market stakeholders, and AI researchers.
The goal of this workshop is to serve the focal point for a wide range of AI researchers and industry practitioners who have informed opinions on agentic systems. This interdisciplinary assembly is crucial for stimulating discussions that blend market design and economics with practical insights from the auctions and finance sector. We envision ICML as the perfect platform to nurture a scientific understanding of agentic markets. It is also the prime setting for enabling influential decision-makers and researchers to exchange knowledge and receive feedback, thereby facilitating impactful changes in the real world.
Speakers
Costis Daskalakis
MIT
Gabriele Farina
MIT
Sumitra Ganesh
JP Morgan
Ian Gemp
Google DeepMind
Gillian Hadfield
University of Toronto
Stefanos Leonardos
King's College London
Barnabe Monnot
Ethereum Foundation
Tuomas Sandholm
CMU
Nathan Worsley
Convexity
Lucas Baker
Jump Trading
Organizing COmmittee
Xyn Sun
Flashbots
Christian Schroeder de Witt
University of Oxford
Ani Calinescu
University of Oxford
Georgios Piliouras
Google DeepMind & SUTD
Thomas Thiery
Ethereum Foundation
Hawra Milani
The Code People
Klaudia Krawiecka
Meta
Dawn Song
University of California, Berkeley
Sponsors
Program Chair
Georgios Piliouras, Google DeepMind & SUTD
Senior Area Chair
Christian Schroeder de Witt, University of Oxford
Area Chair
Xyn Sun, Flashbots
Stefanos Leonardos, King's College London
Thomas Thiery, Ethereum Foundation
Maarten Peter Scholl, University of Oxford
Program Committee
Hao Zhou, University of Oxford
Maarten Peter Scholl, University of Oxford
Hawra Milani, Royal Holloway University of London
Hunar Batra, University of Oxford
Lars Lien Ankile, Massachusetts Institute of Technology
Klaudia Krawiecka, Meta Platforms
John Lazarsfeld, Yale
Blas Kolic, IMDEA Networks
Constantin Venhoff, University of Oxford
Stefanos Leonardos, King's College London, University of London
Sumeet Ramesh Motwani, University of California, Berkeley
Rupali Bhati, Northeastern University
Ian Gemp, Google DeepMind
Ilayda Canyakmaz, Singapore University of Technology and Design
Aishwarya Majumder, Facebook
Lewis Hammond, University of Oxford
Swapneel S Mehta, New York University
Aymeric Vie, University of Oxford
Imran Mahmood Hashmi, University of Oxford
Igor Krawczuk, Swiss Federal Institute of Technology Lausanne
Angira Sharma, University of Oxford
Uljad Berdica, University of Oxford
Stratis Skoulakis, EPFL - EPF Lausanne
Guohao Li, University of Oxford
Matt Stephenson, Columbia University
Esben Kran, Apart Research
Georgios Chionas, University of Liverpool
Joel Dyer, University of Oxford
Brandon Gary Kaplowitz, New York University
Iosif Sakos, Singapore University of Technology and Design
Ryann Sim, Singapore University of Technology and Design
Tianxin Ning, Facebook
Mallesh Pai, Rice University
Matt Stephenson, Pantera Capital
Carmine Ventre, King's College London, University of London
Andrew Miller, University of Illinois at Urbana-Champaign
Sarisht Wadhwa, Duke University
Agostino Capponi, Columbia University
Gerry Tsoukalas, Boston University
Lin William Cong, Cornell University
Jacob Leshno, University of Chicago
Fahad Saleh, University of Florida
Zhiguo He, Stanford University