Mohammad T. Irfan — accepted AI-conference papers

2025

Pure and Strong Nash Equilibrium Computation in Compactly Representable Aggregate Games

Jared Soundy, Mohammad T. Irfan, Hau Chan

UAI 2025

Aggregate games model interdependent decision making when an agent’s utility depends on their own choice and the aggregation of everyone’s choices. We define a compactly representable subclass of aggregate games we call additive aggregate games, which encompasses popular games like congestion games,

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2024

Equilibrium Computation in Multidimensional Congestion Games: CSP and Learning Dynamics Approaches

Mohammad T. Irfan, Hau Chan, Jared Soundy

UAI 2024poster

We present algorithms of two flavors{—}one rooted in constraint satisfaction problems (CSPs) and the other in learning dynamics{—}to compute pure-strategy Nash equilibrium (PSNE) in k-dimensional congestion games (k-DCGs) and their variants. The two algorithmic approaches are driven by whether or no…

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