New Techniques for the Control of Multi-Agent Systems in Uncertain Environments

不确定环境下多智能体系统控制新技术

• 批准号: 0500234
• 负责人: Venkatachalam Anantharam
• 金额: $ 30.46万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-01 至 2009-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0500234&HistoricalAwards=false
• 关键词: New; Techniques; Control; Multi; Agent

New techniques for the control of multi-agent systems in uncertain environments"ABSTRACTThe research develops new techniques for the control of multi-agent systems in uncertain environments. The problem area is of critical national and scientific importance, since modern engineered systems deployed for many critical applications are comprised of multiple agents who need to coordinate their actions to achieve a control objective in an uncertain environment. Such systems are used for many applications, including surveillance, environmental monitoring, inventory control, and control in hazardous environments, among many others, in fields such as transportation, medical diagnostics, civil engineering, communications networks, and defense systems.The main scientific ideas being developed are (1) a new technique to tame the complexity of controlling multi-agent systems by a focus on aggregate behavior, i.e. not so much on which agent carries out a given action as on how many agents carry out a given action, and (2) a new technique to based on the use of common randomness between the agents to increase their ability to hedge against uncertainty in the environment.The aggregation techniques to tame complexity that are being developed rely on mean-field methods, which have proven well-suited to exposing phase transitions in physical systems, but have so far not been systematically used for control. The phenomenon of symmetry breaking, which occurs when different portions of a homogeneous system must use different control rules to obtain optimal system wide performance, is of particular interest. The techniques to hedge against uncertainty that are being developed rely on game-theoretic models, as well as methods to extract common randomness from ambient noise and the randomized choices of other agents.

【摘要】本课题为不确定环境下多智能体系统的控制开发了新技术。该问题领域具有重要的国家和科学意义，因为用于许多关键应用的现代工程系统由多个代理组成，这些代理需要协调它们的行动以在不确定的环境中实现控制目标。这种系统用于许多应用，包括监视，环境监测，库存控制和危险环境中的控制，以及许多其他领域，如运输，医疗诊断，土木工程，通信网络和国防系统。正在发展的主要科学思想是：(1)一种新的技术，通过关注聚合行为来驯服控制多智能体系统的复杂性，即不是关注哪个智能体执行给定的动作，而是关注有多少智能体执行给定的动作；(2)一种基于智能体之间的共同随机性的新技术，以增加它们抵御环境不确定性的能力。正在开发的抑制复杂性的聚合技术依赖于平均场方法，该方法已被证明非常适合于暴露物理系统中的相变，但迄今尚未系统地用于控制。对称性破缺的现象尤其令人感兴趣，当一个同质系统的不同部分必须使用不同的控制规则来获得最佳的系统范围性能时，就会发生对称性破缺。正在开发的对冲不确定性的技术依赖于博弈论模型，以及从环境噪声和其他代理的随机选择中提取常见随机性的方法。