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.

中文翻译：

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基于 CBR 的系统建模的方法论方法

人工智能 (AI) 已被用于各个领域，以支持系统优化并在复杂性使得使用算法和启发式方法具有挑战性的情况下找到解决方案。基于案例的推理（CBR）是一种人工智能技术，在管理、医学、设计、建筑、零售和智能电网等领域得到了广泛的应用。CBR 是一种解决问题的技术，通过使用过去的经验来获取新知识。CBR 部署的主要挑战之一是目标系统建模过程。本文提出了一种使用抽象模型和具体模型概念对基于 CBR 的应用进行建模的直接方法论方法。用两个模型拆分建模过程有助于在应用领域和 CBR 技术之间分配专业知识。