CASL:用于复杂自适应系统建模的声明性领域特定语言

Lachlan Birdsey, Claudia Szabo, K. Falkner
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引用次数: 10

摘要

复杂自适应系统(CAS)在许多领域中无处不在,例如社交网络、供应链和智能城市。目前,CAS的建模和分析依赖于用于多智能体仿真的自适应技术,这种方法缺乏CAS建模的几个关键特征,例如由其他智能体组成的智能体,以及考虑自适应方法。此外,许多现有的方法不能很好地扩展,从而使它们难以用于分析实际场景。在本文中,我们提出了复杂自适应系统语言(CASL),这是一种声明性语言,能够捕捉到CAS的显著特征,同时又足够通用,可以跨多个领域使用。CASL简化了复杂模型的构建,我们的代码生成方法允许CASL模型在各种平台上执行。我们通过实现三个不同的模型来演示CASL的灵活性,然后使用Repast执行这些模型。
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CASL: A declarative domain specific language for modeling Complex Adaptive Systems
Complex adaptive systems (CAS) are ubiquitous across many domains, such as social networks, supply chains, and smart cities. Currently, the modeling and analysis of CAS relies on adapting techniques used for multi-agent simulation, an approach which lacks several features crucial to CAS modeling, such as agents comprised of other agents, and considering methods for adaptation. Moreover, many existing approaches do not scale well, thus making them difficult to employ in analyzing realistic scenarios. In this paper, we propose the Complex Adaptive System Language (CASL), a declarative language that is able to capture the salient features of CAS while being general enough to be used across multiple domains. CASL facilitates the construction of complex models and our code generation method allows CASL models to be executed on a variety of platforms. We demonstrate the flexibility of CASL by implementing three distinct models, which are then executed using Repast.
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