Collaborative Research: Complex Networks Optimization

合作研究：复杂网络优化

• 批准号: 0217371
• 负责人: Alfredo Garcia
• 金额: $ 6.8万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-01 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0217371&HistoricalAwards=false
• 关键词: Collaborative; Research; Complex; Networks; Optimization

This research project will study optimization algorithms rooted in the ideas of game theory in the context of complex network optimization, and particularly decentralized network optimization. Probably the central issue in managing such decentralized networks has been how to set prices so as to motivate the competing users to evolve to an overall system optimal configuration. The research will investigate the powerful paradigm of economic competition in the framework of artificial dynamic games that are played off-line, resulting in an algorithm that is potentially practical for large-scale systems optimization. The basic paradigm that will be investigated derives from Fictitious Play which is an adaptive procedure wherein each player assumes that other players will play according to the empirical distribution of their previous plays. The Fictitious Play method is a novel paradigm for optimization that draws from several distinct disciplines and application areas, including classical optimization, game theory, transportation science, and queueing network protocols. The robust nature of the algorithm allows for the ill-structured black box models of real systems which seldom exhibit the kind of smoothness properties that classical optimization methods demand. Its applicability in the context of two important real-world systems: a) internet traffic routing protocols and b) dynamic route guidance will be tested. Complex networks optimization is an important capability in a society increasingly dominated by ever more complex networks of people and machines. Examples include intelligent transportation systems, computer networks, and supply chains of customers and suppliers. The success of the research will lead to the development of a theoretical basis for the optimization of such complex-structured systems. The applicability of the proposed algorithmic paradigm of game theory through its application to realistic problems arising in the design and operation of the communications and transportation networks will be tested and refined. This research will not only lead to potential improvements in these application arenas but will also necessitate significant interactions with industry and government to insure realism for the models and data developed.

该研究项目将研究基于复杂网络优化的游戏理论思想的优化算法，尤其是分散的网络优化。管理此类分散网络的主要问题可能是如何设定价格，以激励竞争用户发展为整体系统最佳配置。该研究将在人工动态游戏的框架内调查经济竞争的强大范式，该游戏脱机，导致了一种算法，该算法对于大规模系统优化而言可能实用。将进行研究的基本范式源自虚拟的游戏，这是一个自适应过程，其中每个玩家都认为其他玩家将根据以前的比赛的经验分布进行比赛。虚拟游戏方法是一种新颖的优化范式，可从几个不同的学科和应用领域（包括经典优化，游戏理论，运输科学和排队网络协议）中获取。该算法的强大性质允许实现真实系统的黑匣子模型，这些模型很少表现出经典优化方法所需的那种平滑性属性。它在两个重要的现实系统的上下文中的适用性：a）Internet流量路由协议和b）将测试动态路线指南。复杂的网络优化是越来越复杂的人和机器网络越来越控制的社会中的重要能力。示例包括智能运输系统，计算机网络以及客户和供应商的供应链。研究的成功将导致发展这种复杂结构系统的理论基础。拟议的游戏理论算法范式的适用性通过其应用于在通信和运输网络的设计和操作中产生的现实问题，将进行测试和完善。这项研究不仅将导致这些应用领域的潜在改进，而且还需要与行业和政府进行重大互动，以确保为开发的模型和数据提供现实主义。