STATISTICAL ANALYSIS OF Carma MODELS: AN ADVANCED TUTORIAL

STATISTICAL ANALYSIS OF Carma MODELS: AN ADVANCED TUTORIAL
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DOI：
10.1109/wsc.2018.8632456
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发表时间：
2018-12
期刊：
2018 Winter Simulation Conference (WSC)
影响因子：
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通讯作者：
Vashti Galpin;Anastasis Georgoulas;M. Loreti;Andrea Vandin
Vashti Galpin;Anastasis Georgoulas;M. Loreti;Andrea Vandin
中科院分区：
其他
文献类型：
--
作者：
Vashti Galpin;Anastasis Georgoulas;M. Loreti;Andrea Vandin

文献摘要

相似文献

Carma（集体自适应资源共享马尔可夫智能体）是一种基于过程代数的定量语言，用于对集体自适应系统进行建模。Carma模型由一个环境组成，在这个环境中，一组具有属性存储的组件通过单播和广播通信进行交互，从而提供了丰富的建模形式。Carma模型的语义由连续时间马尔可夫链给出，该链可以使用Carma Eclipse插件进行模拟。此外，统计模型检查可以应用于通过使用Multi-VeStA工具模拟生成的轨迹。本高级教程将介绍一些理论背后的Carma和MultiVeStA，以及演示其应用到集体自适应系统建模。
Carma (Collective Adaptive Resource-sharing Markovian Agents) is a process-algebra-based quantitative language developed for the modeling of collective adaptive systems. A Carma model consists of an environment in which a collective of components with attribute stores interact via unicast and broadcast communication, providing a rich modeling formalism. The semantics of a Carma model are given by a continuous-time Markov chain which can be simulated using the Carma Eclipse Plug-in. Furthermore, statistical model checking can be applied to the trajectories generated through simulation using the Multi-VeStA tool. This advanced tutorial will introduce some of the theory behind Carma and MultiVeStA as well as demonstrate its application to collective adaptive system modeling.