An Existence Result for Hierarchical Stackelberg v/s Stackelberg Games
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Abstract (arXiv)
In Stackelberg v/s Stackelberg games a collection of leaders compete in a Nash game constrained by the equilibrium conditions of another Nash game amongst the followers. The resulting equilibrium problems are plagued by the nonuniqueness of follower equilibria and nonconvexity of leader problems whereby the problem of providing sufficient conditions for existence of global or even local equilibria remains largely open. Indeed available existence statements are restrictive and model specific. In this paper, we present what is possibly the first general existence result for equilibria for this class of games. Importantly, we impose no single-valuedness assumption on the equilibrium of the follower-level game. Specifically, under the assumption that the objectives of the leaders admit a quasi-potential function, a concept we introduce in this paper, the global and local minimizers of a suitably defined optimization problem are shown to be the global and local equilibria of the game. In effect existence of equilibria can be guaranteed by the solvability of an optimization problem, which holds under mild and verifiable conditions. We motivate quasi- potential games through an application in communication networks.
Key facts. Cited by 6 papers in the map (data through 13 Oct 2026). First posted on arXiv 31 Dec 2013.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 1; 2024: 1; 2025: 1.
6 papers.
- 2024HM3: Hierarchical Multi-Objective Model Merging for Pretrained Modelscited by 8
- 2022A Survey of Decision Making in Adversarial Gamescited by 3
- 2021Multi-Leader Congestion Games with an Adversarycited by 1
- 2022Personalized incentives as feedback design in generalized Nash equilibrium problemscited by 1
- 2023GNEP Based Dynamic Segmentation and Motion Estimation for Neuromorphic Imagingcited by 0
- 2025Collab-Solver: Collaborative Solving Policy Learning for Mixed-Integer Linear Programmingcited by 0
- 2025Collab-Solver: Collaborative Solving Policy Learning for Mixed-Integer Linear Programming5 Aug 2025
- 2024HM3: Hierarchical Multi-Objective Model Merging for Pretrained Models27 Sep 2024
- 2023GNEP Based Dynamic Segmentation and Motion Estimation for Neuromorphic Imaging5 Jul 2023
- 2022A Survey of Decision Making in Adversarial Games16 Jul 2022
- 2022Personalized incentives as feedback design in generalized Nash equilibrium problems24 Mar 2022
- 2021Multi-Leader Congestion Games with an Adversary14 Dec 2021