FeatureSim: Feature-driven simulation for exploratory analysis with agent-based models

L. Yilmaz
{"title":"FeatureSim: Feature-driven simulation for exploratory analysis with agent-based models","authors":"L. Yilmaz","doi":"10.1109/DISTRA.2017.8167674","DOIUrl":null,"url":null,"abstract":"Complex simulations are often explained in terms of their features. However, the disconnect between such high-level analysis features and their ad hoc realization in a simulation program impedes effectively conducting exploratory analysis across the structural and representational space of the problem domain. Motivated by the significant role that exploratory analysis plays in computational discovery across a broad range of domains from scientific problem solving to policy analysis, a feature-driven simulation modeling strategy is introduced. The strategy leverages the concept of activity, agent, and feature algebras, allowing flexible run-time as well as design-time composition of agent-based simulation programs in terms of features.","PeriodicalId":109971,"journal":{"name":"2017 IEEE/ACM 21st International Symposium on Distributed Simulation and Real Time Applications (DS-RT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/ACM 21st International Symposium on Distributed Simulation and Real Time Applications (DS-RT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DISTRA.2017.8167674","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Complex simulations are often explained in terms of their features. However, the disconnect between such high-level analysis features and their ad hoc realization in a simulation program impedes effectively conducting exploratory analysis across the structural and representational space of the problem domain. Motivated by the significant role that exploratory analysis plays in computational discovery across a broad range of domains from scientific problem solving to policy analysis, a feature-driven simulation modeling strategy is introduced. The strategy leverages the concept of activity, agent, and feature algebras, allowing flexible run-time as well as design-time composition of agent-based simulation programs in terms of features.
FeatureSim:使用基于代理的模型进行探索性分析的特征驱动仿真
复杂的模拟通常用它们的特征来解释。然而,这种高级分析特性和它们在模拟程序中的临时实现之间的脱节阻碍了在问题域的结构和表示空间中有效地进行探索性分析。探索性分析在从科学问题解决到政策分析的广泛领域的计算发现中发挥着重要作用,因此引入了一种特征驱动的仿真建模策略。该策略利用了活动、代理和特征代数的概念,允许灵活地在运行时和设计时组合基于代理的仿真程序的特性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信