Machine learning an artificial intelligence approach volume II
Machine learning an artificial intelligence approach volume II
The formation and use of abstract concepts in design
Concept formation knowledge and experience in unsupervised learning
Artificial intelligence in engineering design (Vol. II): models of innovative design, reasoning about physical systems, and reasoning about geometry
Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Knowledge Compilation: A Symposium
IEEE Expert: Intelligent Systems and Their Applications
Special Issue: Machine Learning in Design
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Design synthesis knowledge and inductive machine learning
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Dimensions of machine learning in design
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
A foundation for machine learning in design
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Designing creative artificial systems
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
On transferring and sharing design intent using STEP methodology
International Journal of Computer Applications in Technology
Computer based pedestrian landscape design using decision tree templates
Advanced Engineering Informatics
Putting the crowd to work in a knowledge-based factory
Advanced Engineering Informatics
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Machine-learning in design offers tremendous potential to actively support designers in all of their problem-solving and knowledge-requirement activities. This article surveys what designers and their systems have accomplished so far using machine-learning techniques. Previous experiences hold a wealth of knowledge that we often take for granted but use every day. In design, those experiences can play a crucial role in the success or failure of a design project, influencing the quality, cost, and development time of a product. But how can we empower computer-based design systems to acquire this knowledge? How would we use such systems to support design? This article outlines how researchers have applied and developed machine-learning techniques to support design--in particular, how systems use previous designs and how they learn the design process.