A machine learning decision support system for collaborative design

The copyright law of the United States (title 17, U.S. Code) governs the making of photocopies or other reproductions of copyrighted material. Any copying of this document without permission of its author may be prohibited by law. Abstract The research described in this paper is motivated by the complexity surrounding the development of decision support systems (DSSs) for collaborative design processes. If one realizes that each design agent engaged in a collaborative design process may have a unique theory of product behavior , a distinct language of communication, ami a specific model of decision making, the complexity of building a DSS for such a design process is obvious. In this paper, we propose that machine learning is probably the only feasible approach to build a DSS for certain classes of collabo-rative design problems. We discuss high-level requirements for such a DSS and then propose a conceptual solution to build such a DSS based on a machine learning approach.