一种基于智能体的离散事件建模与关联生命仿真语言

IF 0.7 4区 计算机科学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Oliver Reinhardt, Tom Warnke, A. Uhrmacher
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引用次数: 7

摘要

在基于智能体的建模和仿真中,离散时间方法占主导地位。虽然需要在连续时间内覆盖代理的动态,但常用的基于代理的建模框架对离散事件仿真的支持很少。在这里,我们提出了ML3语言的形式化语法和语义,用于将多智能体系统建模和模拟为离散事件系统。该语言侧重于人口统计学中的应用,例如迁移过程,并考虑这一学科的具体要求。其中包括生命历程相互联系的重要性以及活动和事件的年龄依赖性。该语言发展的抽象语法结合了代理的隐喻和受保护的命令。其语义由广义半马尔可夫过程定义。具体语言已被实现为外部特定于领域的语言。我们讨论了高效仿真算法的含义,并阐明了正式定义用于建模和仿真的领域特定语言的好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Language for Agent-based Discrete-event Modeling and Simulation of Linked Lives
In agent-based modeling and simulation, discrete-time methods prevail. While there is a need to cover the agents’ dynamics in continuous time, commonly used agent-based modeling frameworks offer little support for discrete-event simulation. Here, we present a formal syntax and semantics of the language ML3 (Modeling Language for Linked Lives) for modeling and simulating multi-agent systems as discrete-event systems. The language focuses on applications in demography, such as migration processes, and considers this discipline’s specific requirements. These include the importance of life courses being linked and the age-dependency of activities and events. The developed abstract syntax of the language combines the metaphor of agents with guarded commands. Its semantics is defined in terms of Generalized Semi-Markov Processes. The concrete language has been realized as an external domain-specific language. We discuss implications for efficient simulation algorithms and elucidate benefits of formally defining domain-specific languages for modeling and simulation.
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来源期刊
ACM Transactions on Modeling and Computer Simulation
ACM Transactions on Modeling and Computer Simulation 工程技术-计算机:跨学科应用
CiteScore
2.50
自引率
22.20%
发文量
29
审稿时长
>12 weeks
期刊介绍: The ACM Transactions on Modeling and Computer Simulation (TOMACS) provides a single archival source for the publication of high-quality research and developmental results referring to all phases of the modeling and simulation life cycle. The subjects of emphasis are discrete event simulation, combined discrete and continuous simulation, as well as Monte Carlo methods. The use of simulation techniques is pervasive, extending to virtually all the sciences. TOMACS serves to enhance the understanding, improve the practice, and increase the utilization of computer simulation. Submissions should contribute to the realization of these objectives, and papers treating applications should stress their contributions vis-á-vis these objectives.
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