CPS: Small: Collaborative Research: Information Design and Price Mechanisms in Platforms for Cyber-Physical Systems with Learning Agents

CPS：小型：协作研究：具有学习代理的网络物理系统平台中的信息设计和价格机制

• 批准号: 1931696
• 负责人: Ramesh Johari
• 金额: $ 20万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1931696&HistoricalAwards=false
• 关键词: CPS; Small; Collaborative; Research; Information

The goal of this project is new theory for architectures for crowdsourced markets for cyber-physical systems (CPS), such as power systems and shared vehicle systems. A technology-enabled platform digitally mediates transactions between buyers (e.g., energy consumers/riders) and sellers (e.g., generators/drivers) helping to determine prices and pair buyers and sellers. Large-scale CPS impose fundamental physical constraints than traditional 'cyber' platforms, including environmental uncertainty, spatial difference, delay, and limited resources. The broader impacts of the work include mentoring with high-school students and teachers.The project aims to develop guidance for optimal platform design. A central challenge is the complex behavior of agents, which possess limited information and receive limited feedback about how their actions translate to payoffs, and learn continuously over time to discover optimal strategies. The focus of the project is on the design of two significant levers available to the platform: information feedback and price-setting mechanisms. The research agenda is divided into two thrusts: (1) characterization of the dynamical behavior of agents under limited feedback; and (2) platform design through information sharing and pricing. In the first thrust, each agent is assumed to use a reasonable, `natural' learning algorithm and the goal is to understand how mechanisms available to the platform impact the learning process and eventual collective behavior. Outcomes from the first thrust will feed directly into the second, where the primary aim is to design information mechanisms to supplement pricing in order to shape the aggregate behavior of agents.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目的目的是针对网络物理系统（CPS）的众包市场建筑的新理论，例如电力系统和共享车辆系统。一个支持技术的平台通过数字方式调节买方（例如能源消费者/骑手）和卖方（例如发电机/驱动程序）之间的交易，以帮助确定价格和配对买卖双方。与传统的“网络”平台相比，大规模的CPS具有基本的物理约束，包括环境不确定性，空间差异，延迟和资源有限。这项工作的更广泛影响包括与高中生和老师进行指导。该项目旨在为最佳平台设计制定指南。一个核心挑战是代理人的复杂行为，这些行为具有有限的信息，并收到有关其行为如何转化为回报的有限反馈，并随着时间的流逝而不断学习以发现最佳策略。该项目的重点是该平台可用的两个重要杠杆的设计：信息反馈和价格设定机制。研究议程分为两个推力：（1）在有限的反馈下，代理的动力学行为表征； （2）通过信息共享和定价设计平台设计。在第一个推力中，假定每个代理使用合理的“自然”学习算法，目标是了解平台可用的机制如何影响学习过程和最终的集体行为。第一个推力的结果将直接进入第二个，主要目的是设计信息机制来补充定价，以塑造代理的总体行为。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来通过评估来获得支持的。

项目成果

Experimental Design in Two-Sided Platforms: An Analysis of Bias

两侧平台的实验设计：偏差分析

• DOI: 10.1145/3391403.3399507
• 发表时间: 2020
• 期刊: ACM Economics and Computation (EC
• 作者: Johari, Ramesh;Li, Hannah;Weintraub, Gabriel
• 通讯作者: Weintraub, Gabriel