Artificial Intelligence
Data Science
Algorithms
archimedes-Artificial Intelligence, Data Science, Algorithms-greece
greece
Algorithms
Data Science
Artificial Intelligence
[Mechanism Design Theme invited talk] The Complexity of Symmetric Equilibria in Min-Max Optimization and Team Zero-Sum Games
Dates
2025-02-19 14:50 - 16:00
Venue
Artemidos 1 - Amphitheater
Title: The Complexity of Symmetric Equilibria in Min-Max Optimization and Team Zero-Sum Games
Speaker: Ioannis Panageas (UC Irvine)
Abstract: We consider the problem of computing stationary points in min-max optimization, with a particular focus on the special case of computing Nash equilibria in (two-)team zero-sum games. We first show that computing ε-Nash equilibria in 3-player
adversarial team games -- wherein a team of 2 players competes against a single adversary -- is CLS-complete, resolving the complexity of Nash equilibria in such settings. Our proof proceeds by reducing from symmetric ε-Nash equilibria in symmetric, identical-payoff,
two-player games, by suitably leveraging the adversarial player so as to enforce symmetry -- without disturbing the structure of the game. In particular, the class of instances we construct comprises solely polymatrix games, thereby also settling a question
left open by Hollender, Maystre, and Nagarajan (2024). We also provide some further results concerning equilibrium computation in adversarial team games.
Moreover, we establish that computing symmetric (first-order) equilibria in \emph{symmetric} min-max optimization is PPAD-complete, even for quadratic functions. Building on this reduction, we further show that computing symmetric ε-Nash equilibria in symmetric,
6-player (3 vs. 3) team zero-sum games is also PPAD-complete, even for ϵ=poly(1/n). As an immediate corollary, this precludes the existence of symmetric dynamics -- which includes many of the algorithms considered in the literature -- converging to stationary
points. Finally, we prove that computing a non-symmetric poly(1/n)-equilibrium in symmetric min-max optimization is FNP-hard.
Short Bio: Ioannis Panageas is an Assistant Professor of Computer Science at UC Irvine and a researcher at Archimedes
Research unit. He is interested in the theory of computation, machine learning and its interface with non-convex optimization, dynamical systems, learning in games, statistics and multi-agent reinforcement learning. Before joining UCI, he was an Assistant
Professor at Singapore University of Technology and Design. Prior to that he was a MIT postdoctoral fellow. He received his PhD in Algorithms, Combinatorics and Optimization from Georgia Tech in 2016, a Diploma in EECS from National Technical University of
Athens, and a MS in Mathematics from Georgia Tech. He is the recipient of the 2019 NRF fellowship for AI.
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Meeting ID: 364 928 182 762
Passcode: w24fHy
Vision
To position Greece as a leading player in AI and Data Science
Mission
To build an AI Excellence Hub in Greece where the international research community can connect, groundbreaking ideas can thrive, and the next generation of scientists emerges, shaping a brighter future for Greece and the world
Welcome to ARCHIMEDES, a vibrant research hub connecting the global AI and Data Science research community fostering groundbreaking research in Greece and beyond. Its dedicated core team, comprising lead researchers, affiliated researchers, Post-Docs, PhDs and interns, is committed to advancing basic and applied research in Artificial Intelligence and its supporting disciplines, including Algorithms, Statistics, Learning Theory, and Game Theory organized around 8 core research areas. By collaborating with Greek and Foreign Universities and Research Institutes, ARCHIMEDES disseminates its research findings fostering knowledge exchange and providing enriching opportunities for students. Leveraging AI to address real-world challenges, ARCHIMEDES promotes innovation within the Greek ecosystem and extends its societal impact. Established in January 2022, as a research unit of the Athena Research Center with support from the Committee Greece 2021, ARCHIMEDES is funded for its first four years by the EU Recovery and Resilience Facility (RRF).
Christos Papadimitriou Speaks on “Artificial Intelligence: its History, its Present, and its Uncertain Future”
24 March 2026
Christos Papadimitriou, Donovan Family Professor of Computer Science at Columbia Engineering at Columbia University, USA, and Principal Scientist at the Archimedes Research Unit of the Athena Research Center, Greece, spoke about “Artificial Intelligence: its History, its Present, and its Uncertain Future” during the ten-year anniversary event of diaNEOsis think tank, which took place on March 11, 2026, at the Stavros Niarchos Foundation Cultural Center (SNFCC).
Vasia Papanikou to Present the MIMOSA Fairness Exploration Tool at EDBT/ICDT 2026 Joint Conference
24 March 2026
Vasia Papanikou, a PhD student at the University of Ioannina and an Academic fellow at Archimedes, Athena Research Center, Greece, will be demonstrating "MIMOSA: A Tool for Fairness Exploration Through Explanations" at the 29th International Conference on Extending Database Technology (EDBT/ICDT 2026), taking place from March 24–27, 2026, at Tampere, Finland.
Archimedes Academic Fellow Andreas Lolos Presents Research at WACV 2026
16 March 2026
Archimedes Academic Fellow and a third-year PhD student at the National and Kapodistrian University of Athens in Greece, Andreas Lolos recently travelled to Tucson in Arizona, USA, and presented the paper "SGPMIL: Sparse Gaussian Process Multiple Instance Learning" at the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2026).
6 Accepted Papers at ICLR 2026
11 March 2026
The Archimedes research unit of the Athena Research Center in Greece has six papers accepted at this year's International Conference on Learning Representations (ICLR) gathering, including one oral presentation. The acceptance rate for posters was about 25,8% and about 1,1% for oral presentations. Please bear in mind that ICLR, along with NeurIPS and ICML, is considered one of the three top-tier artificial intelligence and machine learning conferences in the world.
The project “ARCHIMEDES Unit: Research in Artificial Intelligence, Data Science and Algorithms” with code OPS 5154714 is implemented by the National Recovery and Resilience Plan “Greece 2.0” and is funded by the European Union – NextGenerationEU.
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