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Enhancing Robustness of Information through Distributed Adaptive Coordination

通过分布式自适应协调增强信息的鲁棒性

基本信息

批准号：
9812755
负责人：
Victor Lesser
金额：
$ 40.15万
依托单位：
University of Massachusetts Amherst
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
1998
资助国家：
美国
起止时间：
1998-09-01 至 2002-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=9812755&HistoricalAwards=false
关键词：
Enhancing Robustness Information through Distributed

项目摘要

The goal of this research project, a collaborative award with IIS-9812764, is to create and disseminate a software infrastructure for building complex and large-scale information systems that are both distributed and robust. The path to such systems lies in viewing distributed information systems as multi-agent systems: computational organizations consisting of potentially hundreds of intelligent real-time agents. Robust information systems will adapt both their functions and performance in response to changes in system goals, changes in performance requirements, and changes in the available software and hardware resources. A multi-agent architecture appropriate for such systems is being developed that contains component technologies for local agent scheduling, multi-agent coordination, organizational design, detection and diagnosis of inappropriate behavior in face of environmental change, and on-line learning to improve the performance of the other components. To evaluate this research, a multi-agent simulation testbed is being utilized to conduct extensive evaluation of the individual technologies, an integrated system prototype, and the issues of scalability to large agent societies. The impact of this work is to provide software, techniques and empirical studies that will facilitate the construction of the next generation of robust information systems.http://dis.cs.umass.edu/

该研究项目的目标是与IIS-9812764合作，旨在创建和传播一个软件基础设施，用于构建分布式和健壮的复杂大型信息系统。通往这样的系统的道路在于将分布式信息系统视为多代理系统：由潜在的数百个智能实时代理组成的计算组织。健壮的信息系统将根据系统目标的变化、性能要求的变化以及可用软件和硬件资源的变化来调整其功能和性能。一个多代理体系结构适合这样的系统正在开发，包含组件技术的本地代理调度，多代理协调，组织设计，检测和诊断不适当的行为，面对环境的变化，和在线学习，以提高其他组件的性能。为了评估这项研究，一个多智能体仿真试验平台正在利用进行广泛的评估的个别技术，一个集成的系统原型，以及可扩展性的问题，以大型代理社会。这项工作的影响是提供软件，技术和实证研究，这将有助于建设下一代强大的信息systems.http://dis.cs.umass.edu/