Topic
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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TL;DR: A Stackelberg Equilibrium framework is proposed to analyze the game between the defender and the attacker under two different types of incomplete information to find the optimal power schedule for the wireless communication network under Denial-of-Service (DoS) attacks.
47 citations
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TL;DR: This paper proposes an one-leader one-follower Stackelberg (OLOFS) game model in the presence of multiple eavesdroppers, where optimal power allocation and pricing strategy can be determined to maximize the players' utilities and a distributed learning algorithm is proposed to achieve the equilibrium of the proposed games.
47 citations
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TL;DR: In this paper, an integrated inventory model that allows Stackelberg game policy for optimizing joint total cost of a vendor and buyer system is presented, in which the players of the integrated model are with unequal power (as leader and follower) and the game strategy is utilized to solve this model for obtaining global optimum solution over the finite planning horizon.
Abstract: This paper formulates an integrated inventory model that allows Stackelberg game policy for optimizing joint total cost of a vendor and buyer system. After receiving the lot, the buyer commences an inspection process to determine the defective items. All defective items the buyer sends to vendor during the receiving of the next lot. Due to increasing number of shipments fixed and variable transportation, as well as carbon emissions, are considered, which makes the model sustainable integrated model forever. To reduce the setup cost for the vendor, a discrete setup reduction is considered for maximization more profit. The players of the integrated model are with unequal power (as leader and follower) and the Stackelberg game strategy is utilized to solve this model for obtaining global optimum solution over the finite planning horizon. An illustrative numerical example is given to understand this model clearly.
47 citations
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22 Jul 2012TL;DR: This paper presents PROTECT, a game-theoretic system deployed by the United States Coast Guard in the port of Boston for scheduling their patrols, and offers five key innovations, including a departure from the assumption of perfect adversary rationality and a quantal response model of the adversary's behavior.
Abstract: Building upon previous security applications of computational game theory, this paper presents PROTECT, a game-theoretic system deployed by the United States Coast Guard (USCG) in the port of Boston for scheduling their patrols. USCG has termed the deployment of PROTECT in Boston a success, and efforts are underway to test it in the port of New York, with the potential for nationwide deployment.
PROTECT is premised on an attacker-defender Stackelberg game model and offers five key innovations. First, this system is a departure from the assumption of perfect adversary rationality noted in previous work, relying instead on a quantal response (QR) model of the adversary's behavior -- to the best of our knowledge, this is the first real-world deployment of the QR model. Second, to improve PROTECT's efficiency, we generate a compact representation of the defender's strategy space, exploiting equivalence and dominance. Third, we show how to practically model a real maritime patrolling problem as a Stackelberg game. Fourth, our experimental results illustrate that PROTECT's QR model more robustly handles real-world uncertainties than a perfect rationality model. Finally, in evaluating PROTECT, this paper provides real-world data: (i) comparison of human-generated vs PROTECT security schedules, and (ii) results from an Adversarial Perspective Team's (human mock attackers) analysis.
46 citations
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TL;DR: In this paper, the authors develop conditions for the Takayama-Judge spatial equilibrium model to collapse into the classical Cournot model and implement the spatial equilibrium Cournot Model with linear complementarity programming.
46 citations