Congestion games are attractive because they can model many concrete situations where some competing entities interact through the use of some shared resources, and also because they always admit pure Nash equilibria which correspond to the local minima of a potential function. We explore the problem of computing a state of minimum potential in this setting. Using the maximum number of resources that a player can use at a time, and the possible symmetry in the players' strategy spaces, we settle the complexity of the problem for instances having monotone (i.e., either non-decreasing or non-increasing) latency functions on their resources. The picture, delineating polynomial and NP-hard cases is complemented with tight approximation algorithms.
Short Bio:
Christos Tsoufis is a 2nd year Ph.D. researcher in Computer Science at Université Paris Dauphine - PSL, specializing in algorithmic game theory, combinatorial optimization, and theoretical machine learning, under the supervision of CNRS Researchers Angelo Fanelli and Laurent Gourvès. His research explores computational approaches to approximate stable outcomes in games and multi-agent systems. Christos holds an integrated Master’s degree in Electrical and Computer Engineering from the National Technical University of Athens (NTUA), where he graduated with high honours.
