Worcester Polytechnic Institute Electronic Theses and Dissertations Collection

Title page for ETD etd-050406-145255


Document Typethesis
Author NameMilette, Greg P
Email Address gregorym at gmail.com
URNetd-050406-145255
TitleAnalogical Matching Using Device-Centric and Environment-Centric Representations of Function
DegreeMS
DepartmentComputer Science
Advisors
  • David C. Brown, Advisor
  • George Heineman, Reader
  • Michael Gennert, Department Head
  • Keywords
  • Analogy
  • Design
  • Functional Modeling
  • Functional Reasoning
  • Knowledge Representation
  • Repertory Grid
  • SME
  • Structure Mapping Engine
  • AI in design
  • Date of Presentation/Defense2006-03-30
    Availability unrestricted

    Abstract

    Design is hard and needs to be supported by software. One of the ways software can support designers is by providing analogical reasoning. To make analogical reasoning work well, the software makers need to know how to create a knowledge representation that will facilitate the kind of analogies that the designers want. This thesis will inform software makers by experimenting with two kinds of knowledge representations, called device-centric (DC) and environment-centric (EC), and to try to determine the relative benefits of using either one of them for analogical matching. We performed computational experiments, using Structure Mapping Engine for matching, to determine the quantity and quality of analogical matches that are produced when the representation is varied. We conducted a limited human experiment, using questionnaires and repertory grids, to determine if any of the computational results were novel, and to determine if the human similarity ratings between devices correlated with the computer results. We show that design software should use DC representations to produce a few focused matches which have high average weight. It should use EC representations to produce many matches some of high weight and some of low weight. Based on our human experiment, design software can use either DC or EC representations to produce novel matches. Our experiments also show that human matches correlate most strongly with a combined DC and EC representation and that their similarity reasons are more EC than DC. This suggests that designers tend to think more in EC terms than in DC terms.

    Files
  • milette.pdf

  • Browse by Author | Browse by Department | Search all available ETDs

    [WPI] [Library] [Home] [Top]

    Questions? Email etd-questions@wpi.edu
    Maintained by webmaster@wpi.edu