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

Federico Cannerozzi & Giorgio Ferrari

Mathematics of Operations Research2026https://doi.org/10.1287/moor.2024.0519article
AJG 3ABDC A
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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, whereas 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, whereas the treatment of mean-field coarse correlated equilibria necessitates a new, specifically tailored definition for the stationary setting. Funding: The authors acknowledge financial support from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) [Project-ID 317210226– SFB 1283]. F. Cannerozzi acknowledges financial support from the European Union—NextGenerationEU [Grant NRRP-CUP G53D23006840001].

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@article{federico2026,
  title        = {{Cooperation, Correlation, and Competition in Ergodic N -Player Games and Mean-Field Games of Singular Controls: A Case Study}},
  author       = {Federico Cannerozzi & Giorgio Ferrari},
  journal      = {Mathematics of Operations Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1287/moor.2024.0519},
}

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