图像场景化:从概念模型到可执行仿真

François Rioux, M. Lizotte
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引用次数: 0

摘要

基于代理的建模已被证明是表达各种类型的问题或情况的自然方法。一些研究集中在智能体模型的分析和设计上,但很少有研究真正解决了从最初的问题理解创建基于智能体的模型时对自动化辅助的需求。本文提出了一种解决这一差距的方法,并支持生成可执行代理模型的迭代过程。特别是,这种方法支持问题的增量概念表示和代理模型的开发。本文介绍了如何使用预定义的通用场景化词汇表开发基于代理的模型。然后描述了为了利用最初的概念设计和通过消除软件开发技术来促进模型的开发而选择的技术方法。这种方法是一个更广泛的研究项目IMAGE的一部分,该项目提出了一个工具集,支持对复杂情况的协作理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image-Scenarization: From conceptual models to executable simulation
Agent-based modeling has proven to be a natural way to express various types of problems or situations. Some research has focused on the analysis and design of agent models, but little has truly addressed the need for automated assistance when creating agent-based models from the initial problem comprehension. This paper proposes an approach addressing this gap and supporting the iterative process of generating executable agent models. In particular, this approach enables the incremental conceptual representation of a problem and the development of agent models. This paper presents how to develop an agent-based model using a predefined generic Scenarization Vocabulary. It then describes the technical approach that was chosen in order to exploit the initial conceptual design and facilitate the development of models by eliminating software development technicalities. This approach is part of a broader research effort known as IMAGE, which proposes a toolset supporting collaborative understanding of complex situations.
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