IndShaker:一种基于知识的方法来增强多视角系统动力学分析

S. F. Pileggi
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引用次数: 0

摘要

作为系统动力学分析结果的决策制定,在实践中需要一个直接的和系统的建模能力,以及高层次的定制和灵活性,以适应可能彼此差异很大的情况和环境。虽然一般来说,完全通用的方法可能不如特别的解决方案有效,但由于定性和定量方面的巧妙结合,现代技术的适当应用可能促进敏捷战略。为了解决这种复杂性,我们提出了一种基于知识的方法,该方法将异构标准的系统计算与开放语义相结合。参考体系结构描述了对框架的整体理解,所开发的概念验证原型可以支持高级系统分析,并且适用于许多应用程序上下文,例如:,作为研究/教育工具、沟通框架、游戏化和参与式模型。此外,基于知识的理念(基于语义Web技术)通过互操作性提高了整体知识构建和重用的能力。最后但并非最不重要的是,该框架旨在在未来不断发展,例如通过合并更先进的人工智能功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IndShaker: A Knowledge-Based Approach to Enhance Multi-Perspective System Dynamics Analysis
Decision making as a result of system dynamics analysis requires, in practice, a straightforward and systematic modeling capability as well as a high-level of customization and flexibility to adapt to situations and environments that may vary very much from each other. While in general terms a completely generic approach could be not as effective as ad hoc solutions, the proper application of modern technology may facilitate agile strategies as a result of a smart combination of qualitative and quantitative aspects. In order to address such complexity, we propose a knowledge-based approach that integrates the systematic computation of heterogeneous criteria with open semantics. The holistic understanding of the framework is described by a reference architecture and the proof-of-concept prototype developed can support high-level system analysis, as well as being suitable within a number of applications contexts—i.e., as a research/educational tool, communication framework, gamification and participatory modeling. Additionally, the knowledge-based philosophy, developed upon Semantic Web technology, increases the capability in terms of holistic knowledge building and re-use via interoperability. Last but not least, the framework is designed to constantly evolve in the next future, for instance by incorporating more advanced AI-powered features.
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