Games, Decisions & Networks Research Lab

Artificial intelligence (AI) applications are becoming increasingly prevalent in social systems, such as the digital economy and urban mobility. They are now considered socio-technical systems, including human and AI-powered decision-makers. This raises new questions about how AI-powered decision-makers will interact with each other and with humans in such emerging dynamical systems and how we can apply control-theoretic methodologies for their reliable integration into our society. Therefore, at the GDN Lab,

  • We focus on developing a foundational understanding of learning and autonomy in complex, dynamic, and multi-agent systems.
  • We develop new methodologies for analyzing, controlling, and optimizing socio-technical systems.
  • We apply these methodologies to specific problems in urban mobility, robotics, and the digital economy.

See the preprint arXiv:2111.11742, the following poster and the video recording as examples of our recent research projects:

M. O. Sayin, F. Parise, and A. Ozdaglar, “Fictitious play in zero-sum stochastic games,” SIAM Journal on Control and Optimization, 2022.
University of Minnesota, Institute for Mathematics & Its Applications, Data Science Seminar in Apr. 2023

We are looking for new team members. Please get in touch with us if you are interested in!

Recent News

  • [Sep. 2024] Our paper “Team-fictitious play for reaching team-Nash equilibrium in multi-team games” will appear in NeurIPS’24.
  • [Sep. 2024] Our papers “Strategic control of intersections for efficient traffic routing without tolls” and “Strategic control of experience-weighted attraction model in human-AI interactions” will appear in CPHS’24.
  • [Aug. 2024] Yuksel Arslantas presented his M.S. Thesis “Heterogeneity and strategic sophistication in multi-agent reinforcement learning” successfully.
  • [July 2024] Our paper “Generalized individual Q-learning for polymatrix games with partial observations” will appear in IEEE CDC’24.
  • [Jun. 2024] Our paper “(Smooth) fictitious-play in identical-interest stochastic games with independent continuation-payoff estimates” got accepted to the Applied and Computational Mathematics, Special Issue on Control, Teams, and Games (dedicated in honor of Tamer Başar).
  • [Jun. 2024] Our paper “Strategizing against Q-learners: A control-theoretical approach” got accepted to the IEEE Control Systems Letters (L-CSS).
  • [Mar. 2024] Dr. Sayin gave an invited talk titled “Taming the Wild West of AI: Game Theory for Predictable AI Interactions” at the Workshop on Vector Optimization, Active Learning, Design of Experiments, Game Theory and Their Applications.
  • [Dec. 2023] Dr. Sayin gave an invited talk titled “Convergence of Heterogeneous Learning Dynamics in Zero-sum Stochastic Games” at the IEEE Conference on Decision and Control, “Workshop on Control, Game, and Learning Theory for Security and Privacy”. [url]
  • [Oct 2023] Dr. Sayin gave an invited talk titled “Efficient-Q Learning for Stochastic Games” at the Annual INFORMS Meeting, “Algorithmic Learning in Games” Session.
  • [Sep 2023] Dr. Sayin gave an invited talk titled “Convergent Heterogenous Learning for Zero-sum Stochastic Games” at the Annual Allerton Conference.