CI-P: Workshop on Enhancing a Large-scale Multiagent Simulation Tool

CI-P：增强大规模多智能体模拟工具研讨会

• 批准号: 1205626
• 负责人: Sean Luke
• 金额: $ 9.95万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1205626&HistoricalAwards=false
• 关键词: CI; Workshop; Enhancing; Large; scale

MASON is an open source massive multiagent simulation toolkit, that is, a set of software tools designed to make it easy to build simulations of large numbers of agents -- robots, people, organizations, animals, etc. -- interacting with one another in a complex fashion. Such toolkits are used by scientists to model everything from schools of fish, to swarms of flying robots, to the rise of historic trade routes in Asia. These kinds of models are becoming increasing popular both in the scientific and engineering communities as computer power is enabling the study of large numbers of "agents" to interact with one another in interesting and nontrivial ways. MASON is considered to lie at the "high performance" end of software of this type: it runs on everything from laptops to supercomputers. As such it has become a popular tool for simulating thousands, even potentially millions of agents interacting with one another. MASON is now at a turning point in its development. Models are being developed which are pushing it to its limits, MASON's complexity is proving daunting to newcomers, and it is increasingly attractive to use MASON in the context of massive model optimization. A MASON workshop is intended to solicit community and expert feedback and input on extending and improving MASON in at least three potential ways: 1. A massively distributed version of MASON enables the library to harness large clusters of computers for even bigger and more costly models. 2. Connecting MASON with Integrated Development Environments, and developing a lightweight model development language can make it much easier for non-experts to use MASON. 3. Integration with large-scale stochastic optimization toolkits enables scientists to use MASON as a kind of modeler's assistant: the modeler specifies the high-level rules he believes to be true or wishes to test, and provides an assessment procedure for model output, and then the optimizer proceeds to "fill in the gaps", hunting for the remaining model rules which produce models which optimize this assessment procedure. Similar tools enable sweeps of model parameters. Output from the workshop will go towards development of a community-based plan and methodology to improve MASON in these and other aspects.Tools and techniques like MASON are having an increasing and unusually broad impact on society at large: they're used in large economic and financial models, social models of terrorist networks, game development and special effects, air traffic control, and ecological models ranging from coral reef damage to the impacts of climate change.

Mason是一个开源的大型多智能体模拟工具包，也就是一组软件工具，旨在轻松地构建大量智能体的模拟--机器人、人、组织、动物等--以一种复杂的方式彼此交互。这样的工具包被科学家用来模拟从鱼群到成群的飞行机器人，再到亚洲历史上的贸易路线的崛起。这类模型在科学界和工程界正变得越来越受欢迎，因为计算机的能力使研究大量的“代理人”能够以有趣和非平凡的方式相互作用。梅森被认为是这类软件的“高性能”端：它可以在从笔记本电脑到超级计算机的所有设备上运行。因此，它已经成为一种流行的工具，用于模拟数千甚至数百万个代理之间的相互作用。梅森目前正处于发展的转折点。正在开发的模型正在将其推向极限，Mason的复杂性对新手来说是令人望而生畏的，在大规模模型优化的背景下使用Mason越来越有吸引力。Mason研讨会旨在通过至少三种可能的方式征求社区和专家对扩展和改进Mason的反馈和意见：1.Mason的大规模分布式版本使图书馆能够利用大型计算机集群来实现更大、更昂贵的型号。2.将Mason与集成开发环境连接起来，开发轻量级的模型开发语言，可以让非专家更容易地使用Mason。3.与大型随机优化工具包的集成使科学家能够将Mason用作建模者的一种助手：建模者指定他认为正确或希望测试的高级规则，并为模型输出提供评估程序，然后优化器继续“填补空白”，寻找剩余的模型规则，生成优化该评估程序的模型。使用类似的工具可以扫掠模型参数。研讨会的成果将用于开发基于社区的计划和方法，以在这些和其他方面改进梅森。像梅森这样的工具和技术正在对整个社会产生越来越广泛的影响：它们被用于大型经济和金融模型、恐怖分子网络的社会模型、游戏开发和特效、空中交通管制以及从珊瑚礁破坏到气候变化影响的生态模型。