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Stackelberg competition

About: Stackelberg competition is a research topic. Over the lifetime, 6611 publications have been published within this topic receiving 109213 citations.


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Journal ArticleDOI
TL;DR: A bi-level programming model as a static Stackelberg game between nurses and patients within the framework of HHCSC is developed, to utilize capable meta-heuristics reported in the literature as well as hybrid ones.

61 citations

ReportDOI
TL;DR: In this article, the authors developed strategic monetary policies using a standard two-country macro model under flexible exchange rates and compared them to the Pareto optimal cooperative equilibrium, and analyzed the properties of these policies and their welfare implications.
Abstract: This paper develops strategic monetary policies using a standard two-country macro model under flexible exchange rates. The equilibria considered include feedback Nash and feedback Stackelberg, both of which are compared to the Pareto optimal cooperative equilibrium. The optimal policies are obtained as feedback rules in which real money supplies are adjusted to movements in the real exchange rate. The properties of these policies and their welfare implications are analyzed using numerical simulations. The contrast in the present results with those obtained previously for a short-run horizon suggest the importance of both intertemporal and intratemporal tradeoffs in the determination of optimal strategic policies.

61 citations

Proceedings Article
12 Jul 2020
TL;DR: This work provides insights into the optimization landscape of zero-sum games by establishing connections between Nash and Stackelberg equilibria along with the limit points of simultaneous gradient descent and derive novel gradient-based learning dynamics emulating the natural structure of a StACkelberg game using the implicit function theorem.
Abstract: Contemporary work on learning in continuous games has commonly overlooked the hierarchical decision-making structure present in machine learning problems formulated as games, instead treating them as simultaneous play games and adopting the Nash equilibrium solution concept. We deviate from this paradigm and provide a comprehensive study of learning in Stackelberg games. This work provides insights into the optimization landscape of zero-sum games by establishing connections between Nash and Stackelberg equilibria along with the limit points of simultaneous gradient descent. We derive novel gradient-based learning dynamics emulating the natural structure of a Stackelberg game using the implicit function theorem and provide convergence analysis for deterministic and stochastic updates for zero-sum and general-sum games. Notably, in zero-sum games using deterministic updates, we show the only critical points the dynamics converge to are Stackelberg equilibria and provide a local convergence rate. Empirically, our learning dynamics mitigate rotational behavior and exhibit benefits for training generative adversarial networks compared to simultaneous gradient descent.

61 citations

Journal ArticleDOI
TL;DR: In this paper, a decentralized supply chain consisting of a supplier and a retailer facing price and lead-time-sensitive demand is modeled by a Stackelberg game where the supplier determines the capacity and the wholesale price, and the retailer, as a follower, determines the sale prices and lead time.

61 citations

Proceedings ArticleDOI
01 Dec 2017
TL;DR: The model incorporates the network effects in social domain and congestion in network domain which enables us to obtain insights from the sponsored content policy and derives the closedform solution, i.e., equilibrium, and proves its existence and uniqueness in each stage of the game.
Abstract: Sponsored content policy enables a content provider to pay a network operator, and thereby their users access contents from the content provider through network services from the network operator with lower charge. In this paper, we study the interaction among three entities under the sponsored content policy, namely, the network operator or service provider, the content provider and the end-users. We consider a hierarchical three-stage setting to formulate the game theoretic model to analyze the interaction. Using the game model, we derive the user content demand, optimal sponsoring of content provider, and pricing of service provider based on backward induction. The model incorporates the network effects in social domain and congestion in network domain which enables us to obtain insights from the sponsored content policy. We derive the closedform solution, i.e., equilibrium, and prove its existence and uniqueness in each stage of the game. Additionally, we develop an iterative algorithm to obtain the Stackelberg equilibrium of the entire three-stage game. The simulation results indicate that the revenue, profit, and utility of the service provider, content provider, and end-users have been improved to a large extent under the sponsored content policy because of the network effects.

61 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023551
20221,041
2021563
2020557
2019582
2018487