CSR--CSI: Composing Large-Scale Synthetic Environments through Self-Assembly of Heterogeneous Simulations

CSR--CSI：通过异构仿真自组装构建大规模合成环境

• 批准号: 0720677
• 负责人: Alok Chaturvedi
• 金额: $ 32.5万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2010-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0720677&HistoricalAwards=false
• 关键词: CSR; CSI; Composing; Large; Scale

Modeling complex real world problems in the national and homeland security domains require multi-disciplinary thinking and utilize multiple analytical approaches to represent massive numbers of entities, their behaviors, and the emergent interactions among them. As such, the traditional approach to building comprehensive, requirements-driven simulations does not work for such problems. This project uses a Society-based Approach to Integration using a ?shared but self-managed? paradigm, wherein, autonomous members collaborate in a society while sharing only a part of their knowledge. Component simulations self-assemble into realistic synthetic environments. The self-assembly of simulations is achieved through a domain-specific ontology, simulation specifications, and semantic matching between diverse members. New members join an existing society or an existing member modify its interaction needs without requiring the society to reconfigure. Using knowledge discovery, each member determines what aspects of entities in the society to interact with. In this way, a society is automatically configured into a synthetic environment. Broader impacts of this project include: creation and deployment of large scale synthetic environments by bridging new and existing models and simulations from diverse disciplines; leverage knowledge generated by the wider DDDAS community in creating complex synthetic environments at scales and diversity much greater than the state-of-the-art; facilitate rapid integration across diverse systems and paradigms, such as, discrete event simulations with agent based simulations, in a semantically consistent manner; and develop open source technology that will benefit the community at large with broader application to simulation based engineering, education, and decision analytics.

对国家和国土安全领域中复杂的真实的世界问题进行建模需要多学科的思考，并利用多种分析方法来表示大量的实体、它们的行为以及它们之间的紧急交互。因此，构建全面的、需求驱动的模拟的传统方法不适用于此类问题。 该项目采用基于社会的方法来整合使用？共享但自我管理范式，其中，自主成员在社会中合作，同时只分享他们的知识的一部分。组件模拟自组装成逼真的合成环境。仿真的自组装是通过特定领域的本体，仿真规范，不同成员之间的语义匹配。新成员加入现有的社会或现有的成员修改其互动需求，而不需要社会重新配置。使用知识发现，每个成员决定与社会中实体的哪些方面进行交互。这样，一个社会就被自动地配置成一个合成环境。该项目的更广泛影响包括：通过桥接来自不同学科的新的和现有的模型和模拟来创建和部署大规模合成环境;利用更广泛的DDDAS社区产生的知识，以远大于最先进水平的规模和多样性创建复杂的合成环境;以语义一致的方式促进跨不同系统和范例的快速集成，例如离散事件模拟与基于代理的模拟;并开发开源技术，使整个社区受益，并将其广泛应用于基于仿真的工程，教育和决策分析。