A review of the development and future challenges of case-based reasoning

Abstract

Case-based reasoning (CBR), which is based on the cognitive assumption that similar problems have similar solutions, is an important problem-solving and learning method in the field of artificial intelligence. In this article, the development of CBR is mainly reviewed, and the major challenges of CBR are summarized. The paper is organized into four parts. First, the basic framework and concepts of CBR are introduced. Then, the developed technology and innovative work that were formed in solving problems by CBR are summarized. Moreover, the application fields of CBR are sorted. Finally, according to the idea of deep learning and interpretable artificial intelligence, the main challenges for the future development of CBR are proposed.

SolderlessPCB: Reusing Electronic Components in PCB Prototyping through Detachable 3D Printed Housings

“…Recently, HCI researchers have also argued that the design iteration during the prototyping process should also be viewed from a sustainability perspective [37,60]. As most prototyping processes involve multiple iterations, modules and materials are often integrated into the interim results but are rarely reused or recovered [60]. In other words, their lifespan is as short as the duration of the testing process for each prototyping iteration.…”