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/

该研究项目是与 IIS-9812764 的合作奖项，其目标是创建和传播一个软件基础设施，用于构建分布式且稳健的复杂且大规模的信息系统。通向此类系统的途径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。鲁棒的信息系统将调整其功能和性能，以响应系统目标的变化、性能要求的变化以及可用软件和硬件资源的变化。适合此类系统的多智能体架构正在开发中，其中包含用于本地智能体调度、多智能体协调、组织设计、面对环境变化的不当行为的检测和诊断以及用于提高性能的在线学习的组件技术的其他组件。为了评估这项研究，正在利用多智能体模拟测试平台对各项技术、集成系统原型以及大型智能体社会的可扩展性问题进行广泛的评估。这项工作的影响是提供软件、技术和实证研究，以促进下一代强大信息系统的构建。http://dis.cs.umass.edu/