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math.OC2025
A Game-Theoretic Framework for Network Formation in Large Populations
Gokce Dayanikli, Mathieu Lauriere
In this paper, we study a model of network formation in large populations. Each agent can choose the strength of interaction (i.e. connection) with other agents to find a Nash equi…
math.OC2025
Cooperation, Competition, and Common Pool Resources in Mean Field Games
Gokce Dayanikli, Mathieu Lauriere
Mean field games (MFGs) have been introduced to study Nash equilibria in very large population of self-interested agents. However, when applied to common pool resource (CPR) games,…
math.OC2025
Reconciling Discrete-Time Mixed Policies and Continuous-Time Relaxed Controls in Reinforcement Learning and Stochastic Control
Rene Carmona, Mathieu Lauriere
Reinforcement learning (RL) is currently one of the most prominent methods for optimizing dynamical systems, with breakthrough results across various fields. The framework is based…