Davies, J., Nersessian, N. J., & Goel, A. K. May Analogical Problem Solving With Visual Models Jim Davies, Nancy J. Nersessian, Ashok K. Goel {jimmyd, nancyn, Program in Cognitive Science Georgia Institute of Technology

Davies, J., Nersessian, N. J., & Goel, A. K. May Outline Background: where these ideas are coming from Our computational account of visual analogy Examples: radiation problem and Maxwell’s case study

Davies, J., Nersessian, N. J., & Goel, A. K. May Motivation People use analogy and visual reasoning when problem solving –In Scientific theory creation Nersessian’s cognitive-historical analysis of Maxwell –Psychological studies support this

Davies, J., Nersessian, N. J., & Goel, A. K. May This Work This work builds a new, cognitively informed, computational theory of visual analogy for problem solving, one form of which is scientific discovery. We hypothesize that representing problems as visual abstractions facilitates the analogical process in problem solving.

Davies, J., Nersessian, N. J., & Goel, A. K. May Visual Analogy Visual analogy is analogy with visual elements

Davies, J., Nersessian, N. J., & Goel, A. K. May Bitmap Images Neuron432: on Neuron479: off Neuron200: off Neuron136: off Neuron326: on Neuron344: on

Davies, J., Nersessian, N. J., & Goel, A. K. May Symbolic Images Symbolic Image contains square contains circletriangle inside right-of

Davies, J., Nersessian, N. J., & Goel, A. K. May Symbols Are Mapped

Davies, J., Nersessian, N. J., & Goel, A. K. May Goel’s Computational Work Structure-Behavior-Function: Goel et al IDEAL: Bhatta & Goel 1997 – Generic Teleological Mechanisms ToRQUE: Griffith, Nersessian, Goel – Generic Structural Transformations

Davies, J., Nersessian, N. J., & Goel, A. K. May Primitive Visualization Language (Privlan) Primitive visual transformations (privits) Primitive visual elements (privels) Symbolic images (simages)

Davies, J., Nersessian, N. J., & Goel, A. K. May Privits: Primitive Visual Transformations Decompose (object, number) Move (object, new-location)

Davies, J., Nersessian, N. J., & Goel, A. K. May Privels: Primitive Visual Elements Line (thickness, start point, end point) Generic-Visual-Element (size, location)

Davies, J., Nersessian, N. J., & Goel, A. K. May System: Galatea

Davies, J., Nersessian, N. J., & Goel, A. K. May

Davies, J., Nersessian, N. J., & Goel, A. K. May Maxwell’s Model Development

Davies, J., Nersessian, N. J., & Goel, A. K. May Generic Abstraction

Davies, J., Nersessian, N. J., & Goel, A. K. May

Davies, J., Nersessian, N. J., & Goel, A. K. May Primitive Visualization Language (Privlan) Primitive visual transformations (privits) –Add-component, decompose, move Primitive visual elements (privels) –Circle, line, generic-visual-element Symbolic images (simages)

Davies, J., Nersessian, N. J., & Goel, A. K. May Conclusions Galatea has been applied to two examples, supporting our computational theory of visual analogy and Privlan. This implementation has provided support for visual interpretations of the Duncker case and Nersessian’s interpretation of the Maxwell case. We conjecture that visual representations and generic abstractions are useful for a wide variety of problem-solving instances, including scientific discovery.

Davies, J., Nersessian, N. J., & Goel, A. K. May Thank You /visual-analogy/