论文标题
一种基于CBR的系统模型的方法学方法
A Methodological Approach to Model CBR-based Systems
论文作者
论文摘要
人工智能（AI）已在各个领域用于支持系统优化，并找到解决方案，在这些解决方案中，复杂性使使用算法和启发式方法具有挑战性。基于案例的推理（CBR）是一种在管理，医学，设计，建筑，零售和智能网格等领域中进行了大量利用的AI技术。 CBR是解决问题的技术，并通过使用过去的经验来捕获新知识。 CBR部署的主要挑战之一是目标系统建模过程。本文提出了一种直接的方法论方法，可以使用抽象和混凝土模型的概念模拟基于CBR的应用程序。用两个模型将建模过程分解，促进了应用领域和CBR技术之间的专业知识分配。方法论方法旨在促进CBR建模过程并在计算机科学以外的各个领域促进CBR使用。
Artificial intelligence (AI) has been used in various areas to support system optimization and find solutions where the complexity makes it challenging to use algorithmic and heuristics. Case-based Reasoning (CBR) is an AI technique intensively exploited in domains like management, medicine, design, construction, retail and smart grid. CBR is a technique for problem-solving and captures new knowledge by using past experiences. One of the main CBR deployment challenges is the target system modeling process. This paper presents a straightforward methodological approach to model CBR-based applications using the concepts of abstract and concrete models. Splitting the modeling process with two models facilitates the allocation of expertise between the application domain and the CBR technology. The methodological approach intends to facilitate the CBR modeling process and to foster CBR use in various areas outside computer science.
