Abstracts

Jeff's deeply influential work on the Monotonic Concession Protocol is a beautiful example for his efforts to introduce game-theoretical methods into the field of AI. It arguably is the most natural way of formally modelling a negotiation process between two

rational agents, each repeatedly making small concessions until an agreement is found. In this talk I shall briefly recall this idea and its impact on research and teaching in multiagent systems, and then discuss how one might try to extend the basic model to also cover negotiation processes between more than two agents.

Ulle Endriss is Professor of AI and Collective Decision Making at the University of Amsterdam, where he is based at the interdisciplinary Institute for Logic, Language and Computation (ILLC). Much of his research is concerned with the application of ideas originating in computer science to problems arising in economics and politics. He has been a regular at AAMAS since its second edition and served as PC chair in 2021. 

Michael P. Wellman is Professor of Computer Science & Engineering at the University of Michigan. He received a PhD from the Massachusetts Institute of Technology in 1988 for his work in qualitative probabilistic reasoning and decision-theoretic planning. From 1988 to 1992, Wellman conducted research in these areas at the USAF’s Wright Laboratory. For the past 30+ years, his research has focused on computational market mechanisms and game-theoretic reasoning methods, with applications in electronic commerce, finance, and cyber-security. As Chief Market Technologist for TradingDynamics, Inc., he designed configurable auction technology for dynamic business-to-business commerce. Wellman previously served as Chair of the ACM Special Interest Group on Electronic Commerce (SIGecom), and as Executive Editor of the Journal of Artificial Intelligence Research. He is a Fellow of the Association for the Advancement of Artificial Intelligence and the Association for Computing Machinery.

Maria Gini joined the Department of Computer Science & Engineering in 1982 as an assistant professor and was later promoted to a professor. She also served as the associate head of the department from 2005-15. Gini is a member of ACM, IEEE, and the IEEE Robotics Society. She was named a Morse-Alumni Distinguished Teaching Professor in 1987, was named a College of Science & Engineering Distinguished Professor in 2008, was named an IEEE Fellow in 2018, was named an ACM Fellow in 2019, and received the President’s Award for Outstanding Service in 2019. 

Kate Larson is a Professor and holds a University Research Chair in the Cheriton School of Computer Science, University of Waterloo and is a research scientist with Google Deepmind.  She is interested in algorithmic questions arising in artificial intelligence and multiagent systems with a particular focus on algorithmic game theory and computational social choice, group decision making, preference modelling, and the insights that reinforcement learning can bring to these problems, along with ways of promoting and supporting cooperative AI.   

She has received various awards and recognitions for her research and, because she likes seeing cooperation in action,  she has been involved in organizing and supporting many conferences and workshops in different roles, including AAMAS (general chair) and IJCAI (program chair).

One of the first grants I ever received, "Computational Aspects of Social Choice in Multiagent Systems," was joint with Jeff.  It played a formative role in my career, and through it, I got to meet his amazing group, many of them with important roles at this workshop.  I will discuss a less noticed paper from this time (with Michael Zuckerman, Piotr Faliszewski, and Jeff) that brought together computational social choice with cooperative game theory in a natural way.  I will close by considering the implications for cooperative AI today. 

Ariel Procaccia is Gordon McKay Professor of Computer Science at Harvard University. He works on a broad and dynamic set of problems related to AI, algorithms, economics, and society. He has helped create systems and platforms that are widely used to solve everyday fair division problems, resettle refugees, distribute food, and select citizens’ assemblies. To make his research accessible to the public, he has written numerous opinion and exposition pieces for publications such as the Washington Post, Bloomberg, Wired, and Scientific American. He is a AAAI Fellow (2024) and a recipient of the ACM SIGecom Mid-Career Award (2024), Social Choice and Welfare Prize (2020), Guggenheim Fellowship (2018), IJCAI Computers and Thought Award (2015), and Sloan Research Fellowship (2015).