Towards a case-based computational model for the creative design of electromagnetic devices

In order to explore creativity in design, a computational model based on CBR (an approach to employing old experiences to solve new problems) and other soft computing techniques from machine learning, is proposed in this paper. The new model is able to address four challenging issues: generation of a design prototype from incomplete requirements; judgment and improvement of system performance given a sparse initial case base library; extraction of critical features from a given feature space; adaptation of retrieved previous solutions to similar problems for deriving a new solution to a given design task. The core principle employed by this model is that different knowledge from various level cases can be explicitly explored and integrated into a practical design process.