Matching Items (12)

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Random Simulations of Braess's Paradox

Description

This paper uses network theory to simulate Nash equilibria for selfish travel within a traffic network. Specifically, it examines the phenomenon of Braess's Paradox, the counterintuitive occurrence in which adding

This paper uses network theory to simulate Nash equilibria for selfish travel within a traffic network. Specifically, it examines the phenomenon of Braess's Paradox, the counterintuitive occurrence in which adding capacity to a traffic network increases the social costs paid by travelers in a new Nash equilibrium. It also employs the measure of the price of anarchy, a ratio between the social cost of the Nash equilibrium flow through a network and the socially optimal cost of travel. These concepts are the basis of the theory behind undesirable selfish routing to identify problematic links and roads in existing metropolitan traffic networks (Youn et al., 2008), suggesting applicative potential behind the theoretical questions this paper attempts to answer. New topologies of networks which generate Braess's Paradox are found. In addition, the relationship between the number of nodes in a network and the number of occurrences of Braess's Paradox, and the relationship between the number of nodes in a network and a network's price of anarchy distribution are studied.

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Created

Date Created
  • 2015-05

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Using Games to Explore Collective Action on International Scales

Description

One of the salient challenges of sustainability is the Tragedy of the Commons, where individuals acting independently and rationally deplete a common resource despite their understanding that it is not

One of the salient challenges of sustainability is the Tragedy of the Commons, where individuals acting independently and rationally deplete a common resource despite their understanding that it is not in the group's long term best interest to do so. Hardin presents this dilemma as nearly intractable and solvable only by drastic, government-mandated social reforms, while Ostrom's empirical work demonstrates that community-scale collaboration can circumvent tragedy without any elaborate outside intervention. Though more optimistic, Ostrom's work provides scant insight into larger-scale dilemmas such as climate change. Consequently, it remains unclear if the sustainable management of global resources is possible without significant government mediation. To investigate, we conducted two game theoretic experiments that challenged students in different countries to collaborate digitally and manage a hypothetical common resource. One experiment involved students attending Arizona State University and the Rochester Institute of Technology in the US and Mountains of the Moon University in Uganda, while the other included students at Arizona State and the Management Development Institute in India. In both experiments, students were randomly assigned to one of three production roles: Luxury, Intermediate, and Subsistence. Students then made individual decisions about how many units of goods they wished to produce up to a set maximum per production class. Luxury players gain the most profit (i.e. grade points) per unit produced, but they also emit the most externalities, or social costs, which directly subtract from the profit of everybody else in the game; Intermediate players produce a medium amount of profit and externalities per unit, and Subsistence players produce a low amount of profit and externalities per unit. Variables influencing and/or inhibiting collaboration were studied using pre- and post-game surveys. This research sought to answer three questions: 1) Are international groups capable of self-organizing in a way that promotes sustainable resource management?, 2) What are the key factors that inhibit or foster collective action among international groups?, and 3) How well do Hardin's theories and Ostrom's empirical models predict the observed behavior of students in the game? The results of gameplay suggest that international cooperation is possible, though likely sub-optimal. Statistical analysis of survey data revealed that heterogeneity and levels of trust significantly influenced game behavior. Specific traits of heterogeneity among students found to be significant were income, education, assigned production role, number of people in one's household, college class, college major, and military service. Additionally, it was found that Ostrom's collective action framework was a better predictor of game outcome than Hardin's theories. Overall, this research lends credence to the plausibility of international cooperation in tragedy of the commons scenarios such as climate change, though much work remains to be done.

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Created

Date Created
  • 2014-12

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A Market For Television and Internet Content

Description

We develop a unique model for household preferences in a three good market of television content (cable), internet content (Netflix), and income spent on any other good or activity. Utility

We develop a unique model for household preferences in a three good market of television content (cable), internet content (Netflix), and income spent on any other good or activity. Utility is a function of the time spent viewing television content, time spent viewing internet content, and income spent otherwise. Preferences are determined by the complementarity (or substitutability) of television and internet content, the complementarity of viewing content and spending income otherwise, and individual preference for income. Consumers maximize utility subject to time of viewership and budget constraints. We analyze the comparative statics of the model by varying the complementarity between television and internet content and the complementarity between viewing content and spending income otherwise. We develop a model of firms, in which there are two firms offering one product each who compete on price. They charge a flat-fee for their product (either television or internet content) and have a fixed cost. Their revenue is determined by the number of consumers who choose to purchase their product multiplied by the price they charge. We find a collusive outcome for the firms. We analyze the Nash Equilibrium of the model. We only found symmetric Mixed Action Nash Equilibria (MANE), with the following interesting feature: Bertrand Competition causes firms to choose low prices very often, but firms price significantly higher should the price drop too low. Thus, the MANE places high probability mass on the lowest and highest prices of each firm but has little mass elsewhere.

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Created

Date Created
  • 2016-05

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Data Driven Game Theoretic Cyber Threat Mitigation

Description

Penetration testing is regarded as the gold-standard for understanding how well an organization can withstand sophisticated cyber-attacks. However, the recent prevalence of markets specializing in zero-day exploits on the darknet

Penetration testing is regarded as the gold-standard for understanding how well an organization can withstand sophisticated cyber-attacks. However, the recent prevalence of markets specializing in zero-day exploits on the darknet make exploits widely available to potential attackers. The cost associated with these sophisticated kits generally precludes penetration testers from simply obtaining such exploits – so an alternative approach is needed to understand what exploits an attacker will most likely purchase and how to defend against them. In this paper, we introduce a data-driven security game framework to model an attacker and provide policy recommendations to the defender. In addition to providing a formal framework and algorithms to develop strategies, we present experimental results from applying our framework, for various system configurations, on real-world exploit market data actively mined from the darknet.

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Created

Date Created
  • 2016-05

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School choice: Mixed strategy Nash equilibrium as a way to predict preference reporting

Description

Since Abdulkadiroglu and Sonmez’s influential paper in 2003 that
merges school choice and mechanism design, research in the rapidly
growing school choice literature has been mainly focused on the
design

Since Abdulkadiroglu and Sonmez’s influential paper in 2003 that
merges school choice and mechanism design, research in the rapidly
growing school choice literature has been mainly focused on the
design of mechanisms with desirable properties or more realistic
assumptions. However, lab experiments often show that subjects do
not report preferences according to the experimenters’ expectation,
and the experiments rarely provide an in-depth analysis of why the
subjects behave in such confounding ways. My thesis formulates
preference reporting in school choice as a game by incorporating a
payoff schedule and proposes mixed strategy Nash equilibrium as a
way to predict preference reporting.

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Created

Date Created
  • 2019-05

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Institutional analysis of water management for agriculture in the Chancay-Lambayeque basin, Peru

Description

This research presents an analysis of the main institutions and economic incentives that drive farmers behaviors on water use in the Chancay-Lambayeque basin, located in Lambayeque (Peru), a semi arid

This research presents an analysis of the main institutions and economic incentives that drive farmers behaviors on water use in the Chancay-Lambayeque basin, located in Lambayeque (Peru), a semi arid area of great agricultural importance. I focus my research on identifying the underlying causes of non-collaborative behaviors in regard to water appropriation and infrastructure provisioning decision that generates violent conflicts between users. Since there is not an agreed and concrete criteria to assess "sustainability" I used economic efficiency as my evaluative criteria because, even though this is not a sufficient condition to achieve sustainability it is a necessary one, and thus achieving economic efficiency is moving towards sustainable outcomes. Water management in the basin is far from being economic efficient which means that there is some room for improving social welfare. Previous studies of the region have successfully described the symptoms of this problem; however, they did not focus their study on identifying the causes of the problem. In this study, I describe and analyze how different rules and norms (institutions) define farmers behaviors related to water use. For this, I use the Institutional Analysis and Development framework and a dynamic game theory model to analyze how biophysical attributes, community attributes and rules of the system combined with other factors, can affect farmers actions in regard to water use and affect the sustainability of water resources. Results show that water rights are the factor that is fundamental to the problem. Then, I present an outline for policy recommendation, which includes a revision of water rights and related rules and policies that could increase the social benefits with the use of compensation mechanisms to reach economic efficiency. Results also show that commonly proposed solutions, as switch to less water intensive and more added value crops, improvement in the agronomic and entrepreneurial knowledge, or increases in water tariffs, can mitigate or exacerbate the loss of benefits that come from the poor incentives in the system; but they do not change the nature of the outcome.

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Created

Date Created
  • 2013

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Coping with selfish behavior in networks using game theory

Description

While network problems have been addressed using a central administrative domain with a single objective, the devices in most networks are actually not owned by a single entity but by

While network problems have been addressed using a central administrative domain with a single objective, the devices in most networks are actually not owned by a single entity but by many individual entities. These entities make their decisions independently and selfishly, and maybe cooperate with a small group of other entities only when this form of coalition yields a better return. The interaction among multiple independent decision-makers necessitates the use of game theory, including economic notions related to markets and incentives. In this dissertation, we are interested in modeling, analyzing, addressing network problems caused by the selfish behavior of network entities. First, we study how the selfish behavior of network entities affects the system performance while users are competing for limited resource. For this resource allocation domain, we aim to study the selfish routing problem in networks with fair queuing on links, the relay assignment problem in cooperative networks, and the channel allocation problem in wireless networks. Another important aspect of this dissertation is the study of designing efficient mechanisms to incentivize network entities to achieve certain system objective. For this incentive mechanism domain, we aim to motivate wireless devices to serve as relays for cooperative communication, and to recruit smartphones for crowdsourcing. In addition, we apply different game theoretic approaches to problems in security and privacy domain. For this domain, we aim to analyze how a user could defend against a smart jammer, who can quickly learn about the user's transmission power. We also design mechanisms to encourage mobile phone users to participate in location privacy protection, in order to achieve k-anonymity.

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Created

Date Created
  • 2013

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Data-Driven and Game-Theoretic Approaches for Privacy

Description

In the past few decades, there has been a remarkable shift in the boundary between public and private information. The application of information technology and electronic communications allow service providers

In the past few decades, there has been a remarkable shift in the boundary between public and private information. The application of information technology and electronic communications allow service providers (businesses) to collect a large amount of data. However, this ``data collection" process can put the privacy of users at risk and also lead to user reluctance in accepting services or sharing data. This dissertation first investigates privacy sensitive consumer-retailers/service providers interactions under different scenarios, and then focuses on a unified framework for various information-theoretic privacy and privacy mechanisms that can be learned directly from data.

Existing approaches such as differential privacy or information-theoretic privacy try to quantify privacy risk but do not capture the subjective experience and heterogeneous expression of privacy-sensitivity. The first part of this dissertation introduces models to study consumer-retailer interaction problems and to better understand how retailers/service providers can balance their revenue objectives while being sensitive to user privacy concerns. This dissertation considers the following three scenarios: (i) the consumer-retailer interaction via personalized advertisements; (ii) incentive mechanisms that electrical utility providers need to offer for privacy sensitive consumers with alternative energy sources; (iii) the market viability of offering privacy guaranteed free online services. We use game-theoretic models to capture the behaviors of both consumers and retailers, and provide insights for retailers to maximize their profits when interacting with privacy sensitive consumers.

Preserving the utility of published datasets while simultaneously providing provable privacy guarantees is a well-known challenge. In the second part, a novel context-aware privacy framework called generative adversarial privacy (GAP) is introduced. Inspired by recent advancements in generative adversarial networks, GAP allows the data holder to learn the privatization mechanism directly from the data. Under GAP, finding the optimal privacy mechanism is formulated as a constrained minimax game between a privatizer and an adversary. For appropriately chosen adversarial loss functions, GAP provides privacy guarantees against strong information-theoretic adversaries. Both synthetic and real-world datasets are used to show that GAP can greatly reduce the adversary's capability of inferring private information at a small cost of distorting the data.

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Created

Date Created
  • 2018

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The What, When, and How of Strategic Movement in Adversarial Settings: A Syncretic View of AI and Security

Description

The field of cyber-defenses has played catch-up in the cat-and-mouse game of finding vulnerabilities followed by the invention of patches to defend against them. With the complexity and scale of

The field of cyber-defenses has played catch-up in the cat-and-mouse game of finding vulnerabilities followed by the invention of patches to defend against them. With the complexity and scale of modern-day software, it is difficult to ensure that all known vulnerabilities are patched; moreover, the attacker, with reconnaissance on their side, will eventually discover and leverage them. To take away the attacker's inherent advantage of reconnaissance, researchers have proposed the notion of proactive defenses such as Moving Target Defense (MTD) in cyber-security. In this thesis, I make three key contributions that help to improve the effectiveness of MTD.

First, I argue that naive movement strategies for MTD systems, designed based on intuition, are detrimental to both security and performance. To answer the question of how to move, I (1) model MTD as a leader-follower game and formally characterize the notion of optimal movement strategies, (2) leverage expert-curated public data and formal representation methods used in cyber-security to obtain parameters of the game, and (3) propose optimization methods to infer strategies at Strong Stackelberg Equilibrium, addressing issues pertaining to scalability and switching costs. Second, when one cannot readily obtain the parameters of the game-theoretic model but can interact with a system, I propose a novel multi-agent reinforcement learning approach that finds the optimal movement strategy. Third, I investigate the novel use of MTD in three domains-- cyber-deception, machine learning, and critical infrastructure networks. I show that the question of what to move poses non-trivial challenges in these domains. To address them, I propose methods for patch-set selection in the deployment of honey-patches, characterize the notion of differential immunity in deep neural networks, and develop optimization problems that guarantee differential immunity for dynamic sensor placement in power-networks.

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Created

Date Created
  • 2020

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Effect of chaos and complex wave pattern formation in multiple physical systems: relativistic quantum tunneling, optical meta-materials, and co-evolutionary game theory

Description

What can classical chaos do to quantum systems is a fundamental issue highly relevant to a number of branches in physics. The field of quantum chaos has been active for

What can classical chaos do to quantum systems is a fundamental issue highly relevant to a number of branches in physics. The field of quantum chaos has been active for three decades, where the focus was on non-relativistic quantumsystems described by the Schr¨odinger equation. By developing an efficient method to solve the Dirac equation in the setting where relativistic particles can tunnel between two symmetric cavities through a potential barrier, chaotic cavities are found to suppress the spread in the tunneling rate. Tunneling rate for any given energy assumes a wide range that increases with the energy for integrable classical dynamics. However, for chaotic underlying dynamics, the spread is greatly reduced. A remarkable feature, which is a consequence of Klein tunneling, arise only in relativistc quantum systems that substantial tunneling exists even for particle energy approaching zero. Similar results are found in graphene tunneling devices, implying high relevance of relativistic quantum chaos to the development of such devices. Wave propagation through random media occurs in many physical systems, where interesting phenomena such as branched, fracal-like wave patterns can arise. The generic origin of these wave structures is currently a matter of active debate. It is of fundamental interest to develop a minimal, paradigmaticmodel that can generate robust branched wave structures. In so doing, a general observation in all situations where branched structures emerge is non-Gaussian statistics of wave intensity with an algebraic tail in the probability density function. Thus, a universal algebraic wave-intensity distribution becomes the criterion for the validity of any minimal model of branched wave patterns. Coexistence of competing species in spatially extended ecosystems is key to biodiversity in nature. Understanding the dynamical mechanisms of coexistence is a fundamental problem of continuous interest not only in evolutionary biology but also in nonlinear science. A continuous model is proposed for cyclically competing species and the effect of the interplay between the interaction range and mobility on coexistence is investigated. A transition from coexistence to extinction is uncovered with a non-monotonic behavior in the coexistence probability and switches between spiral and plane-wave patterns arise. Strong mobility can either promote or hamper coexistence, while absent in lattice-based models, can be explained in terms of nonlinear partial differential equations.

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Created

Date Created
  • 2012