Artificial intelligence (AI) has been used in various areas to support system\noptimization and find solutions where the complexity makes it challenging to\nuse algorithmic and heuristics. Case-based Reasoning (CBR) is an AI technique\nintensively exploited in domains like management, medicine, design,\nconstruction, retail and smart grid. CBR is a technique for problem-solving\nand captures new knowledge by using past experiences. One of the main CBR\ndeployment challenges is the target system modeling process. This paper\npresents a straightforward methodological approach to model CBR-based applications\nusing the concepts of abstract and concrete models. Splitting the\nmodeling process with two models facilitates the allocation of expertise between\nthe application domain and the CBR technology. The methodological\napproach intends to facilitate the CBR modeling process and to foster CBR\nuse in various areas outside computer science.
Loading....