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Cooperation, Correlation and Competition in Ergodic N-player Games and Mean-field Games of Singular Controls: A Case Study

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arxiv 2404.15079 v2 pith:KRUIG4GF submitted 2024-04-23 math.OC math.PRq-fin.MF

classification math.OCmath.PRq-fin.MF
keywords mean-fieldequilibriagamescontrolplayercasecoarsecontrols
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abstract

We consider a class of $N$-player games and mean-field games of singular controls with ergodic performance criterion, providing a benchmark case for irreversible investment games featuring mean-field interaction and strategic complementarities. The state of each player follows a geometric Brownian motion, controlled additively through a nondecreasing process, while agents seek to maximize a long-term average reward functional with a power-type instantaneous profit, under strategic complementarity. We explore three different notions of optimality, which, in the mean-field limit, correspond to the mean-field control solution, mean-field coarse correlated equilibria, and mean-field Nash equilibria. We explicitly compute equilibria in the three cases and compare them numerically, in terms of yielded payoffs and existence conditions. Finally, we show that the mean-field control and mean-field equilibria can approximate the cooperative and competitive equilibria, respectively, in the corresponding $N$-player game when $N$ is sufficiently large. Our analysis of the mean-field control problem features a novel Lagrange multiplier approach, which proves crucial in establishing the approximation result, while the treatment of mean-field coarse correlated equilibria necessitates a new, specifically tailored definition for the stationary setting.

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  1. Optimal Policy Characterization for a Class of Multi-Dimensional Ergodic Singular Stochastic Control Problems

    math.OC 2025-10 accept novelty 6.0 of 10

    Optimal policy in multi-dimensional ergodic singular control is characterized via Skorokhod reflection at free boundaries of an auxiliary Dynkin game, with two fully solved 2D inventory models.

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