论文标题
部分可观测时空混沌系统的无模型预测
Facilitating automated conversion of scientific knowledge into scientific simulation models with the Machine Assisted Generation, Calibration, and Comparison (MAGCC) Framework
论文作者
论文摘要
机器辅助生成，比较和校准（MAGCC）框架提供了机器的援助，并在开发，实施，测试和使用科学模拟模型中反复的关键步骤和过程自动化。 MAGCC桥接通过自然语言处理或从现有数学模型中提取的知识提取的系统，并提供了一个全面的工作流程，其中包括科学模型和人工智能（AI）辅助代码生成的组成。 MAGCC accomplishes this through: 1) the development of a comprehensively expressive formal knowledge representation knowledgebase, the Structured Scientific Knowledge Representation (SSKR) that encompasses all the types of information needed to make any simulation model, 2) the use of an artificially intelligent logic reasoning system, the Computational Modeling Assistant (CMA), that takes information from the SSKR and generates, in a traceable fashion, model specifications across a range of simulation modeling方法，以及3）使用CMA从这些模型规范中生成可执行代码。可以对任何科学领域进行自定义MAGCC框架，未来的工作将整合新开发的代码生成的AI系统。
The Machine Assisted Generation, Comparison, and Calibration (MAGCC) framework provides machine assistance and automation of recurrent crucial steps and processes in the development, implementation, testing, and use of scientific simulation models. MAGCC bridges systems for knowledge extraction via natural language processing or extracted from existing mathematical models and provides a comprehensive workflow encompassing the composition of scientific models and artificial intelligence (AI) assisted code generation. MAGCC accomplishes this through: 1) the development of a comprehensively expressive formal knowledge representation knowledgebase, the Structured Scientific Knowledge Representation (SSKR) that encompasses all the types of information needed to make any simulation model, 2) the use of an artificially intelligent logic reasoning system, the Computational Modeling Assistant (CMA), that takes information from the SSKR and generates, in a traceable fashion, model specifications across a range of simulation modeling methods, and 3) the use of the CMA to generate executable code for a simulation model from those model specifications. The MAGCC framework can be customized any scientific domain, and future work will integrate newly developed code-generating AI systems.
