Communications of the ACM
Acquiring Graphic Design Knowledge with Nonmonotonic Inductive Learning
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
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Graphic designers and other visual problem solving experts now routinely use computer-based image-editing tools in their work. Recently, attempts have been made to apply learning and inference techniques from artificial intelligence techniques to graphical editors in order to provide intelligent assistance to design professionals. The success of these attempts will depend on whether the programs can successfully capture the design knowledge of their users. But what is the nature of this knowledge? Because AI techniques have usually been applied in such areas as medicine or engineering rather than visual design, little is known about how design knowledge might differ from knowledge in other fields. This paper reports the results of an informal knowledge engineering study to try to understand how knowledge is communicated between humans in graphic design. Nowhere is the process of design communication more critical than in teaching beginning designers, since the effectiveness of the communication is crucial to the success of the student. The study examined books intended to teach graphic design to novices, and tried to analyze the nature of the communication with a view toward applying the results to a knowledge acquisition system for graphic design applications.