CAREER: Game Theoretic Methods for Multiagent Coordination

职业：多智能体协调的博弈论方法

• 批准号: 1638214
• 负责人: Jason Marden
• 金额: $ 37.99万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-02-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1638214&HistoricalAwards=false
• 关键词: CAREER; Game; Theoretic; Methods; Multiagent

A multiagent system can be characterized by a collection of interacting subsystems each making local decisions in response to local information. There are numerous examples of multiagent systems spanning both the engineering and social sciences, e.g., wind farms, surveillance systems, and transportation networks. Regardless of the specific domain, the primary goal in such systems is to design admissible mechanisms for coordinating the behavior of the individual subsystems to ensure that the emergent collective behavior is desirable with respect to a system-level objective. Intellectual Merit The overarching goal of this project is to develop game-theoretic methodologies for multiagent coordination with broad applicability to both social and engineering systems. In the context of social multiagent systems, this project will focus on the derivation of optimal mechanisms for coordinating the collective behavior in situations where the society's sensitivity to such mechanisms is unknown, e.g., taxation mechanisms on traffic networks. In the context of engineering multiagent systems, this project will focus on the derivation of (i) distributed control algorithms that guarantee that the multiagent systems exhibits the optimal correlated behavior and (ii) fundamental relationships pertaining to how informational patterns impact achievable performance guarantees in multiagent systems.Broader ImpactsA central goal on this project involves promoting the general understanding of multiagent systems to the engineering community and beyond. Undoubtedly, engineers will be responsible for the design of a wide array of multiagent systems with examples spanning all aspects of society. Successfully controlling such ?complex? systems requires that engineers be multi-disciplinary with a strong proficiency in both the engineering and social sciences. This project will seek to achieve this goal through direct interactions with K-12 students, public lectures, dissemination of course material at the intersection of social and engineering sciences, and direct interactions with industry to illustrate the applicability of the developed methodologies.

多智能体系统的特点是交互子系统的集合，每个子系统响应本地信息做出本地决策。工程和社会科学领域有许多多智能体系统的例子，例如风电场、监控系统和交通网络。无论具体领域如何，此类系统的主要目标是设计可接受的机制来协调各个子系统的行为，以确保出现的集体行为对于系统级目标而言是理想的。 智力优势 该项目的总体目标是开发多智能体协调的博弈论方法，并广泛适用于社会和工程系统。 在社会多主体系统的背景下，该项目将重点关注在社会对此类机制的敏感性未知的情况下协调集体行为的最佳机制的推导，例如交通网络的税收机制。 在工程多智能体系统的背景下，该项目将重点推导（i）保证多智能体系统表现出最佳相关行为的分布式控制算法，以及（ii）与信息模式如何影响多智能体中可实现的性能保证相关的基本关系更广泛的影响 该项目的一个中心目标是促进工程界及其他领域对多智能体系统的普遍理解。 毫无疑问，工程师将负责设计各种多智能体系统，其示例涵盖社会的各个方面。成功控制这样的“复杂”？系统要求工程师是多学科的，精通工程和社会科学。该项目将寻求通过与 K-12 学生的直接互动、公开讲座、传播社会科学和工程科学交叉领域的课程材料以及与行业的直接互动来说明所开发方法的适用性来实现这一目标。