Capacity Maximization in Cognitive Networks: A Stackelberg Game-Theoretic Perspective

2010 ◽  
Author(s):  
Chungang Yang ◽  
Jiandong Li
Keyword(s):  
Stackelberg Game ◽  
Cognitive Networks ◽  
Capacity Maximization ◽  
Game Theoretic

An Adversarial Agent-Based Design Method Using Stochastic Stackelberg Game Conditions

2021 ◽  
Vol 143 (3) ◽  
Author(s):  
Sean C. Rismiller ◽  
Jonathan Cagan ◽  
Christopher McComb
Keyword(s):  
Stackelberg Game ◽  
Design Method ◽  
Agent Based ◽  
Game Format ◽  
Game Theoretic

Abstract Products must often endure challenging conditions while fulfilling their intended functions. Game-theoretic methods can readily create a wide variety of these conditions to consider when creating designs. This work introduces Cognitively Inspired Adversarial Agents (CIAAs) that use a Stackelberg game format to generate designs resistant to these conditions. These agents are used to generate designs while considering a multidimensional attack. Designs are produced under these adversarial conditions and compared to others generated without considering adversaries to confirm the agents’ performance. The agents create designs able to withstand multiple combined conditions.

Stackelberg Game Theoretic Framework in Cognitive Green Heterogeneous Networks

2017 ◽  
pp. 269-286
Author(s):  
Chungang Yang ◽  
Pengyu Huang ◽  
Jia Xiao ◽  
Lingxia Wang ◽  
Jiandong Li
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Cognitive Radio ◽  
Cellular Networks ◽  
Communication Networks ◽  
Cognitive Radio Networks ◽  
Stackelberg Game ◽  
Radio Networks ◽  
Heterogeneous Cellular Networks ◽  
Game Theoretic

Game theory has found an extensive application in wireless communication networks including cognitive radio networks, heterogeneous cellular networks, cooperative relay networks. Also, cognitive radio networks, green communications and heterogeneous cellular networks have attracted a wide attention on improve the spectrum efficiency and energy efficiency; therefore, the capacity, the coverage and the energy consumption. However, interference problem and energy consumption are critical for these networks. Introducing hierarchy among different decision-making players in cognitive, heterogeneous, green, cooperative cellular networks can both save energy and mitigate interference, thus enhance throughput. Stackelberg game suits to model, analyze and design the distributed algorithms in these hierarchical decision-making networking scenarios. In this chapter, we introduce basics of Stackelberg game and survey the extensive applications of Stackelberg game in cognitive, heterogeneous, cooperative cellular networks with the emphasis on resource management, green commutations design and interference management. This chapter highlights the potentials and applications with the promising vision of Stackelberg game theoretic framework for future cognitive green heterogeneous cellular networks.

Game Theoretic Cloud-Assisted Opportunistic Spectrum Access in Cognitive Radio Networks

2016 ◽  
Vol 8 (2) ◽  
pp. 94-110
Author(s):  
Danda B. Rawat ◽  
Sachin Shetty
Keyword(s):  
Cognitive Radio ◽  
Wide Band ◽  
Cognitive Networks ◽  
Opportunistic Spectrum Access ◽  
Packet Error Rate ◽  
Theoretic Approach ◽  
Spectrum Access ◽  
Secondary Users ◽  
Computational Capacity ◽  
Game Theoretic

Opportunistic Spectrum Access (OSA) in a Cognitive Radio Network (CRN) is regarded as emerging technology for utilizing the scarce Radio Frequency (RF) spectrum by allowing unlicensed secondary users (SUs) to access licensed spectrum without creating harmful interference to primary users (PUs). The SUs are considerably constrained by their limited power, memory and computational capacity when they have to make decision about spectrum sensing for wide band regime and OSA. The SUs in CRN have the potential to mitigate these constraints by leveraging the vast storage and computational capacity of cloud computing approaches. In this paper, the authors investigate a game theoretic approach for opportunistic spectrum access in cognitive networks. The proposed algorithm leverages the geo-locations of both SUs and spectrum opportunities to facilitate OSA to SUs. The active SUs using game theory adapt their transmit powers in a distributed manner based on the estimated average packet-error rate while satisfying the Quality-of-Service (QoS) in terms of signal-to-interference-noise-ratio (SINR). Furthermore, to control greedy SUs in distributed power control game, the authors introduce a manager/leader through a Stackelberg power adaptation game. The performance of the proposed approaches is investigated using numerical results obtained from simulations.

scholarly journals A Game Theoretic Approach for Eco-Design and Remanufacturing Considering Take-Back Policy

2020 ◽  
Vol 12 (17) ◽  
pp. 7174
Author(s):  
Xiaoxiao Chang ◽  
Guangye Xu ◽  
Qian Wang ◽  
Yongguang Zhong
Keyword(s):  
Environmental Impact ◽  
Stackelberg Game ◽  
Theoretic Approach ◽  
Subsidy Policy ◽  
Monetary Value ◽  
Game Equilibrium ◽  
Take Back ◽  
Game Theoretic ◽  
The Government ◽  
Game Theoretic Approach

This paper mainly aims at investigating the governments’ take-back policy of penalty or subsidy that motivates eco-design or remanufacturing. For this purpose, we consider a two-stage Stackelberg game between a government and a manufacturer. The government first decides to impose a take-back penalty or offer a take-back subsidy, and then the manufacturer selects to remanufacture or invest in eco-design as a response to the take-back policy. Upon analyzing and comparing game equilibrium, we find that the government prefers to offer a subsidy policy for eco-design and to impose a penalty policy for remanufacturing. The manufacturer will decide on investing in eco-design when the monetary value of the environmental impact of landfill and eco-design coefficient is medium. However, if the eco-design coefficient is high, the manufacturer practices remanufacturing instead of eco-design whether penalized and subsidized. The present study provides a set of guidelines in practical managerial recommendations for governments and manufacturers.

scholarly journals Game-Theoretic Question Selection for Tests

2017 ◽  
Vol 59 ◽  
pp. 437-462
Author(s):  
Yuqian Li ◽  
Vincent Conitzer
Keyword(s):  
Large Scale ◽  
Stackelberg Game ◽  
Test Taker ◽  
Optimal Test ◽  
Random Strategy ◽  
Special Cases ◽  
Driver's License ◽  
Game Theoretic ◽  
True Ability ◽  
Test Result

Conventionally, the questions on a test are assumed to be kept secret from test takers until the test. However, for tests that are taken on a large scale, particularly asynchronously, this is very hard to achieve. For example, TOEFL iBT and driver's license test questions are easily found online. This also appears likely to become an issue for Massive Open Online Courses (MOOCs, as offered for example by Coursera, Udacity, and edX). Specifically, the test result may not reflect the true ability of a test taker if questions are leaked beforehand. In this paper, we take the loss of confidentiality as a fact. Even so, not all hope is lost as the test taker can memorize only a limited set of questions' answers, and the tester can randomize which questions to let appear on the test. We model this as a Stackelberg game, where the tester commits to a mixed strategy and the follower responds. Informally, the goal of the tester is to best reveal the true ability of a test taker, while the test taker tries to maximize the test result (pass probability or score). We provide an exponential-size linear program formulation that computes the optimal test strategy, prove several NP-hardness results on computing optimal test strategies in general, and give efficient algorithms for special cases (scored tests and single-question tests). Experiments are also provided for those proposed algorithms to show their scalability and the increase of the tester's utility relative to that of the uniform-at-random strategy. The increase is quite significant when questions have some correlation---for example, when a test taker who can solve a harder question can always solve easier questions.

Game-Theoretic Analysis of Pricing Models in a Dyadic Supply Chain With Fairness Concerns

2019 ◽  
Vol 10 (2) ◽  
pp. 1-24 ◽  
Author(s):  
Abhishek Sharma
Keyword(s):  
Supply Chain ◽  
Stackelberg Game ◽  
Channel Coordination ◽  
Theoretic Analysis ◽  
Nash Game ◽  
Game Theoretic Analysis ◽  
Pricing Decisions ◽  
Fairness Concerns ◽  
Game Theoretic ◽  
Fairness Concern

The existing studies on fairness in channel coordination assume markets as the group of oligopolies in which a few firms dominate, scant evidence has been provided where fairness concerns are investigated for a market scenario where all firms share equal dominance. This article considers a dyadic supply chain composed of one fair-minded manufacturer and one fair-minded retailer and investigate their pricing decisions under two different non-cooperative game-theoretic frameworks: manufacturer-led Stackelberg game and Vertical Nash game and provide a comparative analysis. The results show that the prices of the Stackelberg game model are always higher than that of the corresponding prices of the Vertical Nash game. We also find that the prices gap between the two models decreases with the retailer's fairness concern, and is uncertain with respect to manufacturer's fairness. In addition, the manufacturer's (retailer's) profit in the Stackelberg game is decreasing (increasing) in its own fairness and is uncertain in the Vertical Nash game. Furthermore, findings are illustrated through a numerical example.

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