NeTS: Small: PTERA: Prospect Theory Enhanced Resource Allocation

许多实证研究表明，人类评估效用的方式与效用理论并不一致。由诺贝尔经济学奖得主丹尼尔·卡尼曼（Daniel Kahneman）和他的合作者阿莫斯·特沃斯基（Amos Tversky）开创的累积前景理论提供了一个框架，其中包括作为特例的效用理论，它能够捕捉到面对选择时实际观察到的各种人类行为。该项目发展了前景理论模型的含义，即人类如何在通信网络的一些核心问题的背景下评估选择。该项目研究了当选择评估由前景理论最终用户完成时，通信网络协议可能需要如何修改。预计这项研究的结果将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一个参考来衡量的。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，损失的斜率大于参考点附近的收益。前景是一系列可能的收益或损失，每一个都有一定的概率。向用户展示前景，并通过累积前景理论规则对其进行建模评估，这也涉及相对于大概率超重小概率的加权函数。这个项目集中在两个具体的，广泛适用的，并且在通信网络中非常重要的问题类。其中一个问题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。该项目研究如何设计适当的前景呈现给用户，以实现更好的安全目标，因此更安全，更有弹性的网络。第二个问题是弹性用户的网络资源分配问题。该项目研究如何设计与现有协议向后兼容的类tcp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和所使用的网络资源，本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的互动提供了广泛的学科基础。除了通信网络，这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具有更广泛的影响，因为该研究开发了新的累积前景理论研究方法，可用于与这些学科相关的类似场景的分析和设计。这个项目也有重要的教育组成部分，包括培训研究生和为本科生提供一个有研究经验的平台。在这个项目中开展的研究将被纳入随机系统的估计和控制课程，并有望影响网络经济学课程，这两门课程都是在伯克利教授的。该研究为本科生项目提供了机会，特别是通过伯克利EECS部门倡议，通过邀请不同群体的本科生在夏季参加教师的研究项目，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.