NeTS: Small: PTERA: Prospect Theory Enhanced Resource Allocation

大量实证研究表明，人类评估效用的方式与效用理论不一致。累积前景理论由诺贝尔经济学奖获得者丹尼尔·卡尼曼（Daniel Kahneman）和他的合作者阿莫斯·特沃斯基（Amos Tversky）首创，提供了一个框架，其中包括作为特例的效用理论，该框架能够捕获在面临选择时实际观察到的各种人类行为。该项目开发了前景理论模型的含义，以指导人类如何在通信网络的一些核心问题的背景下评估选择。该项目研究当前景理论最终用户进行选择评估时，可能需要如何修改通信网络协议。预计这项研究的结果可能是改善最终用户体验的更好的网络协议。在累积前景理论中，收益和损失是相对于参考值来衡量的。为了使理论与经验观察到的行为一致，用于评估收益和损失的函数对于收益是凹的，对于损失是凸的，损失的斜率比接近参考的收益的斜率更大。前景是可能的收益或损失的列表，每种收益或损失都有一定的概率。用户会看到前景，并通过累积前景理论的规则对其进行建模来评估它们，该理论还涉及相对于大概率而言超重小概率的加权函数。该项目重点关注通信网络中两个具体的、广泛适用的且非常重要的问题类别。其中之一是如何激励用户遵循最佳实践来保护连接到网络的个人设备的问题。该项目研究如何设计适当的前景向用户展示，以实现更安全、更安全、更有弹性的网络的目标。第二个是网络中弹性用户的资源分配问题。该项目研究如何设计与现有协议向后兼容的类似 TCP 的协议，但这将提高前景理论用户的感知效用，同时仍然使用相同的网络资源。通过权衡弹性用户的用户体验与所使用的网络资源，该项目还开发了提高非弹性用户性能的方法。更广泛的影响：决策技术和博弈论技术为研究人类如何与技术系统以及彼此之间互动的广泛学科提供了基础。除了通信网络之外，此类学科的例子还包括经济学和金融学。该项目的成果对这些学科产生了更广泛的影响，因为本研究开发了累积前景理论研究的新方法，可用于与这些单独学科相关的类似场景中的分析和设计。该项目还具有重要的教育成分，包括培训研究生并为本科生提供研究经验的平台。该项目开发的研究将被纳入随机系统估计和控制课程的课程中，预计将对伯克利分校教授的网络经济学课程产生影响。该研究为本科生项目提供了机会，特别是通过伯克利 EECS 部门的举措，通过在暑期邀请不同的本科生群体参与教员的研究项目来促进多样性和包容性。

Numerous empirical studies have shown that humans evaluate utilities in ways that are not consistent with utility theory. Cumulative prospect theory, pioneered by the Nobel prize-winning economist Daniel Kahneman, and his collaborator, Amos Tversky, provides a framework, including utility theory as a special case, which is able to capture a wide range of actually observed human behaviors when faced with choices. This project develops the implications of prospect theoretic models for how humans evaluate choice in the context of some of the core problems of communication networking. The project studies how communication networking protocols may need to be modified when the evaluation of choice is done by prospect-theoretic end users. It is expected that better network protocols that improve the end-user experience could be a result of this research. In cumulative prospect theory, gains and losses are measured relative to a reference. In order to make the theory consistent with empirically observed behavior the function used to evaluate gains and losses is concave for gains and convex for losses, with a larger slope for losses than for gains near the reference. A prospect is a list of possible gains or losses, each with a certain probability. Users are presented with prospects and modeled as evaluating them via the rules of cumulative prospect theory, which also involve weighting functions that overweight small probabilities relative to large probabilities. This project focuses on two specific, widely applicable, and highly important problem classes in communication networking. One of these is the question of how to incentivize users to follow best practices to secure their individual devices that are connected to the network. The project studies how to design the appropriate prospects to present to the users to achieve the goal of a better secured and therefore safer and more resilient network. The second of these is the problem of resource allocation in the network for elastic users. The project studies how to design TCP-like protocols that are backward compatible with the existing ones, but that will improve the perceived utility for prospect-theoretic users while still working with the same network resources. By trading off user experience of elastic users with the network resources used, this project also develops ways to improve the performance for inelastic users. Broader Impacts: Techniques for decision making and game theoretic techniques provide the underpinnings for a broad range of disciplines that study how humans interact with technological systems and with each other. Apart from communication networking, examples of such disciplines include economics and finance. The outcomes of this project have broader impact in these disciplines, because novel methodologies for cumulative prospect theory research that can be used for analysis and design in similar scenarios that are relevant to these individual disciplines are developed in this research. This project also has a significant educational component, including training graduate students and providing a platform for undergraduates to have a research experience. The research developed in this project will be incorporated into the curriculum of the course on estimation and control of stochastic systems and is expected to impact the course on network economics, both taught at Berkeley. The research provides opportunities for undergraduate projects, in particular through the Berkeley EECS departmental initiatives that foster diversity and inclusion by inviting a diverse group of undergraduates during the summers to participate in the research programs of the faculty members.