Professor Rasoul Etesami of the Department of Industrial and Enterprise Systems Engineering for the Grainger College of Engineering has won the SIAM Journal on Control and Optimization (SICON) Best Paper Prize — a prestigious research honor awarded by one of the leading journals in control and applied mathematics. His work advances how independent agents can learn to reach stable outcomes in dynamic environments with limited information — a breakthrough with direct applications in smart grids, communication networks and beyond.
The big picture:
The prize recognizes research at the cutting edge of control theory and optimization — fields critical to systems like smart grids, networked infrastructure and autonomous decision-making.
Game theory underpins many applications, including energy management in smart grids, bandwidth allocation in wireless communication networks, and network security. However, enabling systems of independent and self-interested agents to reach a Nash equilibrium — a stable outcome in which each agent’s decision optimizes its own payoff given the fixed decisions of others — has long been a challenge in dynamic multi-agent decision-making environments.
Etesami's paper tackles a notoriously difficult problem: How can multiple independent decision-makers (players) learn a Nash equilibrium in dynamic stochastic games where they cannot see each other's actions nor directly communicate with each other?
The breakthrough:
In his award-winning paper, "Learning Stationary Nash Equilibrium Policies in n-Player Stochastic Games with Independent Chains", Etesami developed new learning algorithms for the class of stochastic games with independent chains that:
- Help multiple players learn their stationary Nash equilibrium strategies
- Work even under limited feedback information when players only see their own payoffs — not others’ decisions or the rules of the game
- Guarantee convergence in a short amount of time, under realistic conditions
Real-world impact:
This kind of research has direct applications in distributed energy systems, smart grids, communication networks, and dynamic resource allocation problems— where non-cooperative devices or agents must adapt strategies to optimize their own utilities without full visibility of the whole system, while their collective behavior must still converge to a desired, stable outcome.
What’s next:
Etesami will receive the award at the SIAM Conference on Control and Its Applications (CT25) this July in Montreal.
Rasoul Etesami is an Associate Professor in the Department of Industrial and Enterprise Systems Engineering for the Grainger College of Engineering with affiliations with the Department of Electrical and Computer Engineering (ECE) and the Coordinated Science Laboratory (CSL). His research interests include analysis of complex social, communication, and decision-making systems using tools from control and game theory, optimization and learning theory.