通过实验实现语义模型的合成

Danhua Peng, Roland Ewald, A. Uhrmacher
{"title":"通过实验实现语义模型的合成","authors":"Danhua Peng, Roland Ewald, A. Uhrmacher","doi":"10.1145/2601381.2601394","DOIUrl":null,"url":null,"abstract":"Unambiguous experiment descriptions are increasingly required for model publication, as they contain information important for reproducing simulation results. In the context of model composition, this information can be used to generate experiments for the composed model. If the original experiment descriptions specify which model property they refer to, we can then execute the generated experiments and assess the validity of the composed model by evaluating their results. Thereby, we move the attention to describing properties of a model's behavior and the conditions under which these hold, i.e., its semantics. We illuminate the potential of this concept by considering the composition of Lotka-Volterra models. In a first prototype realized for JAMES II, we use ML-Rules to describe and execute the Lotka-Volterra models and SESSL for specifying the original experiments. Model properties are described in continuous stochastic logic, and we use statistical model checking for their evaluation. Based on this, experiments to check whether these properties hold for the composed model are automatically generated and executed.","PeriodicalId":255272,"journal":{"name":"SIGSIM Principles of Advanced Discrete Simulation","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Towards semantic model composition via experiments\",\"authors\":\"Danhua Peng, Roland Ewald, A. Uhrmacher\",\"doi\":\"10.1145/2601381.2601394\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Unambiguous experiment descriptions are increasingly required for model publication, as they contain information important for reproducing simulation results. In the context of model composition, this information can be used to generate experiments for the composed model. If the original experiment descriptions specify which model property they refer to, we can then execute the generated experiments and assess the validity of the composed model by evaluating their results. Thereby, we move the attention to describing properties of a model's behavior and the conditions under which these hold, i.e., its semantics. We illuminate the potential of this concept by considering the composition of Lotka-Volterra models. In a first prototype realized for JAMES II, we use ML-Rules to describe and execute the Lotka-Volterra models and SESSL for specifying the original experiments. Model properties are described in continuous stochastic logic, and we use statistical model checking for their evaluation. Based on this, experiments to check whether these properties hold for the composed model are automatically generated and executed.\",\"PeriodicalId\":255272,\"journal\":{\"name\":\"SIGSIM Principles of Advanced Discrete Simulation\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIGSIM Principles of Advanced Discrete Simulation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2601381.2601394\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIGSIM Principles of Advanced Discrete Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2601381.2601394","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18

摘要

模型发布越来越需要明确的实验描述,因为它们包含了再现模拟结果的重要信息。在模型组合的上下文中,该信息可用于为组合模型生成实验。如果原始实验描述指定了它们引用的模型属性,那么我们就可以执行生成的实验,并通过评估其结果来评估组合模型的有效性。因此,我们将注意力转移到描述模型行为的属性和这些属性所处的条件上,即它的语义。我们通过考虑Lotka-Volterra模型的组成来阐明这一概念的潜力。在为JAMES II实现的第一个原型中,我们使用ML-Rules来描述和执行Lotka-Volterra模型,并使用SESSL来指定原始实验。在连续随机逻辑中描述模型性质,并使用统计模型检验来评估模型性质。在此基础上,自动生成并执行检查这些属性是否适用于组合模型的实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Towards semantic model composition via experiments
Unambiguous experiment descriptions are increasingly required for model publication, as they contain information important for reproducing simulation results. In the context of model composition, this information can be used to generate experiments for the composed model. If the original experiment descriptions specify which model property they refer to, we can then execute the generated experiments and assess the validity of the composed model by evaluating their results. Thereby, we move the attention to describing properties of a model's behavior and the conditions under which these hold, i.e., its semantics. We illuminate the potential of this concept by considering the composition of Lotka-Volterra models. In a first prototype realized for JAMES II, we use ML-Rules to describe and execute the Lotka-Volterra models and SESSL for specifying the original experiments. Model properties are described in continuous stochastic logic, and we use statistical model checking for their evaluation. Based on this, experiments to check whether these properties hold for the composed model are automatically generated and executed.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Hierarchical resource management for enhancing performance of large-scale simulations on data centers Transparent multi-core speculative parallelization of DES models with event and cross-state dependencies The earth system modeling framework: interoperability infrastructure for high performance weather and climate models Modeling and simulation of data center networks Synchronisation for dynamic load balancing of decentralised conservative distributed simulation
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1