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Dynamic Mechanism Design: From Theor...

Zhang, Tao.

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Dynamic Mechanism Design: From Theories to Applications.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Dynamic Mechanism Design: From Theories to Applications./
作者:	Zhang, Tao.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
面頁冊數:	552 p.
附註:	Source: Dissertations Abstracts International, Volume: 85-05, Section: B.
Contained By:	Dissertations Abstracts International85-05B.
標題:	Engineering. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30637834
ISBN:	9798380847544

Dynamic Mechanism Design: From Theories to Applications.
Zhang, Tao.

Dynamic Mechanism Design: From Theories to Applications. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 552 p.

Source: Dissertations Abstracts International, Volume: 85-05, Section: B.

Thesis (Ph.D.)--New York University Tandon School of Engineering, 2023.

As technological integration with society advances, the transformation from traditional infrastructure to cyber-physical social systems (CPSS) becomes evident. The emergence of smart systems across diverse sectors and the advent of technologies like 5G have reshaped real-time decision-making and accelerated cross-domain interactions. Yet, this rapid evolution of CPSS has inadvertently sparked challenges surrounding inefficiency, security, and privacy. These challenges are further magnified by information asymmetries, diverse local objectives, self-interests of various entities, and the looming threat of malicious actors.This thesis presents a comprehensive exploration into the mechanisms and methodologies to influence decision-making models within multi-agent systems, striving to achieve holistic system-wide outcomes in CPSS. The research encompasses both descriptive perspectives for real-world CPSS applications and prescriptive solutions rooted in rigorous mathematical principles, with a spotlight on competitive systems of self-interested agents (i.e., games) in dynamic and stochastic environments.A pivotal segment of this research delves into dynamic mechanism design, tailored for scenarios where agents possess both informational and autonomous advantages. By considering the time evolution of agents' private information, the study establishes pioneering paradigms that extend beyond conventional incentive approaches. Dynamic information design, another cornerstone of this work, extends beyond conventional Bayesian persuasion to explore general-sum stochastic games, wherein agents confront evolving uncertainties and strategically choose from a spectrum of multiple signaling options. A novel dynamic programming principle, underpinned by the ``fixed-point alignment" equilibrium characterization, emerges from this exploration.On the application front, this research develops an ADMM-based dynamic differentially private learning algorithm, emphasizing the temporal preservation of data privacy. Notably, this methodology has been further tailored and applied to collaborative intrusion detection systems over vehicular ad hoc networks (VANET), offering a robust solution to protect vehicle network interactions. Additionally, the research explores the intricacies of market design for privacy data trading, providing a pioneering approach to valuing and exchanging data privacy efficiently. Concurrently, the evolving landscape of cybersecurity underscores the quintessential role of game theory, particularly when countering intelligent and adaptable cyber threats. In summation, this thesis offers an integrative framework and methodologies to navigate, design, and optimize multi-agent systems within the expansive domain of CPSS, seamlessly bridging theoretical constructs with pragmatic applications.In essence, the discoveries elucidated within this dissertation serve as pioneering strides towards an evolving conceptual framework for cyber-physical social systems. This framework bridges the divide between dynamic multi-agent decision-making processes and the intricate interplay of societal constraints, weaving them seamlessly into the fabric of modern technological landscapes.

ISBN: 9798380847544Subjects--Topical Terms:

586835
Engineering.
Subjects--Index Terms:

Stochastic environments

Dynamic Mechanism Design: From Theories to Applications.
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520 $a As technological integration with society advances, the transformation from traditional infrastructure to cyber-physical social systems (CPSS) becomes evident. The emergence of smart systems across diverse sectors and the advent of technologies like 5G have reshaped real-time decision-making and accelerated cross-domain interactions. Yet, this rapid evolution of CPSS has inadvertently sparked challenges surrounding inefficiency, security, and privacy. These challenges are further magnified by information asymmetries, diverse local objectives, self-interests of various entities, and the looming threat of malicious actors.This thesis presents a comprehensive exploration into the mechanisms and methodologies to influence decision-making models within multi-agent systems, striving to achieve holistic system-wide outcomes in CPSS. The research encompasses both descriptive perspectives for real-world CPSS applications and prescriptive solutions rooted in rigorous mathematical principles, with a spotlight on competitive systems of self-interested agents (i.e., games) in dynamic and stochastic environments.A pivotal segment of this research delves into dynamic mechanism design, tailored for scenarios where agents possess both informational and autonomous advantages. By considering the time evolution of agents' private information, the study establishes pioneering paradigms that extend beyond conventional incentive approaches. Dynamic information design, another cornerstone of this work, extends beyond conventional Bayesian persuasion to explore general-sum stochastic games, wherein agents confront evolving uncertainties and strategically choose from a spectrum of multiple signaling options. A novel dynamic programming principle, underpinned by the ``fixed-point alignment" equilibrium characterization, emerges from this exploration.On the application front, this research develops an ADMM-based dynamic differentially private learning algorithm, emphasizing the temporal preservation of data privacy. Notably, this methodology has been further tailored and applied to collaborative intrusion detection systems over vehicular ad hoc networks (VANET), offering a robust solution to protect vehicle network interactions. Additionally, the research explores the intricacies of market design for privacy data trading, providing a pioneering approach to valuing and exchanging data privacy efficiently. Concurrently, the evolving landscape of cybersecurity underscores the quintessential role of game theory, particularly when countering intelligent and adaptable cyber threats. In summation, this thesis offers an integrative framework and methodologies to navigate, design, and optimize multi-agent systems within the expansive domain of CPSS, seamlessly bridging theoretical constructs with pragmatic applications.In essence, the discoveries elucidated within this dissertation serve as pioneering strides towards an evolving conceptual framework for cyber-physical social systems. This framework bridges the divide between dynamic multi-agent decision-making processes and the intricate interplay of societal constraints, weaving them seamlessly into the fabric of modern technological landscapes.
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653 $a Mechanism design
653 $a Vehicular ad hoc networks
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790 $a 1988
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793 $a English
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