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Synthesizing Visual and Action Routines Using Constraint Programming

  • Bonny Banerjee
  • B. Chandrasekaran
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4045)

Abstract

A diagrammatic problem-solver requires a library of visual routines (VRs) and action routines (ARs) – the VRs are used to obtain information of specified types from the diagram and ARs to modify the diagram in specified ways. The VRs/ARs required are unbounded – a new domain may call for new perceptions and actions. We report on progress on our research in building an automated VR/AR synthesis system that would take as input the definition of a new routine in terms of existing routines in the library and well-defined mathematical/logical constraints and synthesize the program for the desired routine using constraint programming. We illustrate the ideas by means of an example.

Keywords

Constraint Programming Action Routine Spatial Constraint Elementary Operation Constraint Solver 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Ullman, S.: Visual routines. Cognition, 97–159 (1984)Google Scholar
  2. 2.
    Chandrasekaran, B., Kurup, U., Banerjee, B., Josephson, J.R., Winkler, R.: An Architecture for Problem Solving with Diagrams. In: Blackwell, A.F., Marriott, K., Shimojima, A. (eds.) Diagrams 2004. LNCS, vol. 2980, pp. 151–165. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  3. 3.
    Hoffmann, C.M., Joan-Arinyo, R.: A Brief on Constraint Solving. Computer-Aided Design and Applications 2(5), 655–664 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bonny Banerjee
    • 1
  • B. Chandrasekaran
    • 1
  1. 1.Laboratory for AI Research, Department of Computer Science and EngineeringThe Ohio State UniversityColumbusUSA

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