Cooperative negotiation in concurrent engineering design
Proceedings of the MIT-JSME workshop on Computer-aided cooperative product development
Issues and Applications of Case Based Reasoning to Design
Issues and Applications of Case Based Reasoning to Design
IEEE Expert: Intelligent Systems and Their Applications
The "What" and "How" of Learning in Design
IEEE Expert: Intelligent Systems and Their Applications
Explanation-Based Generalization: A Unifying View
Machine Learning
Knowledge Acquisition Via Incremental Conceptual Clustering
Machine Learning
Co-Learning and the Evolution of Social Acitivity
Co-Learning and the Evolution of Social Acitivity
Supporting evolution in a multi-agent cooperative design environment
Advances in Engineering Software
Modeling collective learning in design
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Soft computing in engineering design - A review
Advanced Engineering Informatics
Effects of social learning and team familiarity on team performance
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
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Many of the design systems developed in recent years incorporate some machine learning. The number of such systems already available, and the multitude of design learning opportunities that are slowly being revealed, suggest that the time is ripe to attempt to put these developments into a systematic framework. Consequently, in this paper we present a set of dimensions for machine learning in design research. We hope that it can be used as a guide for comparing existing work, and that it may suggest new directions for future exploration in this area.