Nothing Special   »   [go: up one dir, main page]

skip to main content
article

A computational model of visual analogies in design

Published: 01 September 2009 Publication History

Abstract

We present an analysis of the work of human participants in addressing design problems by analogy. We describe a computer program, called Galatea, that simulates the visual input and output of four experimental participants. Since Galatea is an operational computer program, it makes specific commitments about the visual representations and reasoning it uses for analogical transfer. In particular, Galatea provides a computational model of how human designers might be generating new designs by incremental transfer of the problem-solving procedure used in previous design cases.

References

[1]
Learning generic mechanisms for innovative strategies in adaptive design. The Journal of the Learning Sciences. v6 i4. 367-396.
[2]
Visual analogy as a cognitive strategy in the design process: Expert versus novice performance. Journal of Design Research. v4 i2.
[3]
Expertise and the use of visual analogy: Implications for design education. Design Studies. v20. 153-175.
[4]
Perception in chess. Cognitive Psychology. v4 i1. 55-81.
[5]
Craig, D. L. (2001). Perceptual simulation and analogical reasoning in design. Architecture department Doctoral Dissertation, Georgia Institute of Technology. Technical Report GIT-COGSCI-2001/05.
[6]
Croft, D., & Thagard, P. (2002). Dynamic imagery: A computational model of motion and visual analogy. In L. Magnani & N. J. Nersessian (Eds.), Model-based reasoning: Science, technology, and values (pp. 259-274).
[7]
Davies, J. (2004) Constructive adaptive visual analogy. Doctoral Dissertation. College of Computing, Georgia Institute of Technology. Technical Report GIT-COGSCI-2004/3.
[8]
Davies, J., & Goel, A. K. (2001). Visual analogy in problem solving. In Proceedings of the international joint conference on artificial intelligence (pp. 377-382).
[9]
Transfer of problem-solving strategy using Covlan. Journal of Visual Languages and Computing. v18 i2. 149-164.
[10]
Visuospatial re-representation in analogical reasoning. The Open Artificial Intelligence Journal. v2. 11-20.
[11]
Proteus: Visuospatial analogy in problem solving. Knowledge-Based Systems. v27 i7. 636-654.
[12]
A qualitative (experimental and theoretical) study of productive thinking (solving of comprehensible problems). Journal of Genetic Psychology. v33. 264-708.
[13]
A heuristic program to solve geometric analogy problems. In: Minsky, M. (Ed.), Semantic information processing, MIT Press, Cambridge, MA.
[14]
A unified approach to explanation and theory formation. In: Shrager, J., Langley, P. (Eds.), Computational models of scientific discovery and theory formation, Morgan Kaufman, San Meteo, CA. pp. 157-196.
[15]
The structure mapping engine: Algorithm and examples. Artificial Intelligence. v41. 1-63.
[16]
Farah, M. J. (1988). The neuropsychology of mental imagery: Converging evidence from brain-damaged and normal participants. In Spatial cognition-brain bases and development. Erlbaum.
[17]
Engineering and the mind's eye. MIT Press, Cambridge, MA.
[18]
Ferguson, R. W. (1994). MAGI: Analogy-based encoding using regularity and symmetry. In A. Ram & K. Eiselt (Eds.) Proceedings of the 16th annual conference of the cognitive science society (pp. 283-288).
[19]
Telling juxtapositions: Using repetition and alignable difference in diagram understanding. In: Holyoak, K., Gentner, D., Kokinov, B. (Eds.), Advances in analogy research, New Bulgarian University, Sofia. pp. 109-117.
[20]
Ferguson, R. W., & Forbus, K. D. (2000). GeoRep: A flexible tool for spatial representation of line drawings. In Proceedings of the 18th national conference on artificial intelligence. Austin, TX: AAAI Press.
[21]
Qualitative spatial reasoning framework and frontiers. In: Glasgow, J., Narayanan, N.H.A., Chandrasekaran, B. (Eds.), Diagrammatic reasoning, AAAI Press, Austin, TX. pp. 183-202.
[22]
Problem-solving with diagrammatic representations. Artificial Intelligence. v13 i3. 201-230.
[23]
Analogical problem solving. Cognitive Psychology. v12. 306-355.
[24]
Computational imagery. In: Thagard, P. (Ed.), Mind readings, MIT Press, Cambridge, MA.
[25]
Design patterns: An unit of analogical transfer in creative design. Advanced Engineering Informatics. v18 i2. 85-94.
[26]
Visual analogy - A strategy for design reasoning and learning. In: Eastman, C., Newsletter, W., McCracken, M. (Eds.), Design knowing and learning: Cognition in design education, Elsevier, New York. pp. 199-219.
[27]
Griffith, T. W., Nersessian, N. J., & Goel, A. K. (2000). Function-follows-form transformations in scientific problem solving. In Proceedings of the 22nd annual conference of the cognitive science society. Mahwah, NJ: Lawrence Erlbaum Associates.
[28]
Drawing on the back of an envelope: A framework for interacting with application programs by freehand drawing. Computers and Graphics. v24. 835-849.
[29]
Case-based planning: A framework for planning from experience. Cognitive Science.
[30]
Hofstadter, D. R., & Mitchell, M. (1995). The copycat project: A model of mental fluidity and analogy-making. In D. Hofstadter & The Fluid Analogies Research group (Eds.), Fluid concepts and creative analogies (pp. 205-267). Basic Books.
[31]
A computational model of analogical problem solving. In: Vosniadou, S., Ortony, A. (Eds.), Similarity and analogical reasoning, Cambridge University Press, Cambridge. pp. 242-266.
[32]
Analogical mapping by constraint satisfaction. Cognitive Science. v13. 295-355.
[33]
Mental leaps: Analogy in creative thought. MIT Press.
[34]
Hummel, J., & Holyoak, K. J. (1996). Lisa: A computational model of analogical inference and schema induction. In G. Cottrell (Ed.), Proceedings of the 18th annual conference of the cognitive science society.
[35]
Analogy is like cognition: Dynamic, emergent, and context-sensitive. In: Holyoak, K., Gentner, D., Kokinov, B. (Eds.), Advances in analogy research: Integration of theory and data from the cognitive, computational, and neural sciences, NBU Press, Sofia. pp. 96-105.
[36]
Image and brain: The resolution of the imagery debate. MIT Press, Cambridge, MA.
[37]
Why a diagram is (sometimes) worth ten thousand words. Cognitive Science. v11. 65-99.
[38]
McGraw, G., & Hofstadter, D. R. (1993). Perception and creation of alphabetic style. In Artificial intelligence and creativity: Papers from the 1993 spring symposium. AAAI Technical Report SS-93-01, AAAI Press.
[39]
Narayanan, N. H., Suwa, M. & Motoda, H. (1994). How things appear to work: Predicting behaviors from device diagrams. In Proceedings of the 12th national conference on artificial intelligence (pp. 1161-1167). AAAI Press.
[40]
Rehling, J. A. (2001). Letter spirit (part two): Modeling creativity in a visual domain. Indiana University, Ph.D. thesis.
[41]
Schmid, U., & Carbonell, J. (1999). Empirical evidence for derivational analogy. In M. Hahn & S. C. Stoness (Eds.), Proceedings of the 21st annual conference of the cognitive science society.
[42]
Thagard, P., Gochfeld, D., & Hardy, S. (1992). Visual analogical mapping. In Proceedings of the 14th annual conference of the cognitive science society (pp. 522-527). Erlbaum.
[43]
The importance of drawing in the mechanical design process. Computer Graphics. v14 i2. 263-274.
[44]
Prodigy/analogy: Analogical reasoning in general problem solving. EWCBR. 33-52.
[45]
Derivational analogy in PRODIGY: Automating case acquisition, storage, and utilization. Machine Learning. v10 i3. 249-278.
[46]
Visual analogy: Viewing retrieval and mapping as constraint satisfaction. Journal of Applied Intelligence. v25 i1. 91-105.

Cited By

View all
  • (2022)StoryDrawerProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3501914(1-15)Online publication date: 29-Apr-2022
  • (2020)It Is Your Turn: Collaborative Ideation With a Co-Creative Robot through SketchProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376258(1-14)Online publication date: 21-Apr-2020
  • (2019)Relating Cognitive Models of Design Creativity to the Similarity of Sketches Generated by an AI PartnerProceedings of the 2019 Conference on Creativity and Cognition10.1145/3325480.3325488(259-270)Online publication date: 13-Jun-2019
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Cognitive Systems Research
Cognitive Systems Research  Volume 10, Issue 3
September, 2009
123 pages

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 September 2009

Author Tags

  1. Analogy
  2. Artificial intelligence
  3. Case-based reasoning
  4. Cognitive modeling
  5. Design
  6. Diagrammatic reasoning
  7. Transfer
  8. Visual reasoning

Qualifiers

  • Article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 14 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2022)StoryDrawerProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3501914(1-15)Online publication date: 29-Apr-2022
  • (2020)It Is Your Turn: Collaborative Ideation With a Co-Creative Robot through SketchProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376258(1-14)Online publication date: 21-Apr-2020
  • (2019)Relating Cognitive Models of Design Creativity to the Similarity of Sketches Generated by an AI PartnerProceedings of the 2019 Conference on Creativity and Cognition10.1145/3325480.3325488(259-270)Online publication date: 13-Jun-2019
  • (2012)Fractal analogies for general intelligenceProceedings of the 5th international conference on Artificial General Intelligence10.1007/978-3-642-35506-6_19(177-188)Online publication date: 8-Dec-2012
  • (2011)Finding the odd one outProceedings of the 8th ACM conference on Creativity and cognition10.1145/2069618.2069666(289-298)Online publication date: 3-Nov-2011
  • (2011)Representation, indexing, and retrieval of biological cases for biologically inspired designProceedings of the 19th international conference on Case-Based Reasoning Research and Development10.1007/978-3-642-23291-6_25(334-347)Online publication date: 12-Sep-2011

View Options

View options

Get Access

Login options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media