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A framework for design problem-solving

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Abstract

We develop atask-structure for design problem-solving. The task-structure of a complex problemsolving activity such as design is a hierarchical organization of subtasks. For each task in the task-structure, we can then proceed to investigate whatmethods may be available, and what knowledge and inference requirements each of these methods have. Some of the methods may be domain-specific, some of them more generic in character, some may involve traditional computational techniques, and some others may involve searching in a problem space for solutions to the task. However, this systematic process of identifying tasks, methods, and subtasks will help us to see how design as a general problem is solved not by one method or technique but by an opportunistic exploitation of whatever methods are available (i.e., theknowledge required for using a method is available) to help accomplish a subtask. Thus, in principle, very different methods and knowledge can be brought into play in as flexible a way as applicable. For design problem-solving, we provide such an analysis for a family of design methods that we callpropose-verify-critique-modify methods. We end with remarks about how these methods can be flexibly integrated in a control structure that matches the subtasks with methods for which knowledge is available.

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References

  1. Balzer, R., “Transformation Implementation: an Example,”IEEE Trans. Software Engineering, Vol. SE-7, 1981, pp. 3–14

    Google Scholar 

  2. Barstow, D., “A Perspective on Automatic Programming,”The AI Magazine, Vol. 5, No. 5, 1984

  3. Brown, D.C. and B. Chandrasekaran, “Expert Systems for a Class of Mechanical Design Activity,”Knowledge Engineering in Computer-Aided Design, North Holland, 1985, pp. 259–282

  4. Brown, D.C., and B. Chandrasekaran,Design Problem Solving: Knowledge Structures and Control Strategies, Morgan Kaufmann, San Mateo, California, 1989

    Google Scholar 

  5. Chandrasekaran, B., “Generic Tasks in Knowledge-Based Reasoning: High-Level Building Blocks for Expert System Design,”IEEE Expert, Vol. 1, No. 3, 1986, pp. 23–30

    Google Scholar 

  6. Dixon, J. R., M. K. Simmons and P. R. Cohen, “An Architecture for Application of Articial Intelligence to Design,”Proceedings of the 21st Design Automation Conference, IEEE, 1984, pp. 634–640

  7. Freeman, P. and A. Newell, “A Model for Functional soning in Design,”Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI, 1971, p 621

  8. Friedland, P., “Knowledge-Based Experimental Design in Molecular Genetics,”Proceedings of the 6th International Joint Conference in Artificial Intelligence, IJCAI, Kokyo, Japan, 1979, pp. 285–287

    Google Scholar 

  9. Goel, A. and B. Chandrasekaran, “Use of Device Models in Adaptation of Design Cases,”Proceedings of the Second DARPA Case-Based Reasoning Workshop, Pensacola, Florida, May 1989, pp. 100–109

  10. Goel, A. and B. Chandrasekaran, “Functional Representation of Designs and Redesign Problem Solving,”Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit, Michigan, 1989, pp. 1388–1394, Los Altos, CA: Morgan Kaufmann

    Google Scholar 

  11. Hammond, K.J.,Case-Based Planning: Viewing Planning as a Memory Task, Academic Press, San Diego, 1989

    Google Scholar 

  12. Herman, D.J.,DSPL++: A High-Level Language for Building Design Expert Systems with Flexible Use of Multiple Methods (tentative title), Ph.D. dissertation, The Ohio State University, Department of Computer and Information Science, forthcoming

  13. Johnson, L. and E. Soloway, “PROUST: Knowledge-Based Program Understanding,”IEEE Trans. Softw. Eng., Vol. 11, No. 3, 1985, pp. 267–275

    Google Scholar 

  14. Josephson, J., B. Chandrasekaran, J. Smith and M. Tanner, “A Mechanism for Forming Composite Explanatory Hypotheses,”IEEE Trans. System, Man & Cybernetics, May/June 1987, pp. 445–454

  15. Kelly, V.E. and L.I. Steinberg, “The CRITTER System: Analyzing Digital Circuits by Propagating Behaviors and Specifications,”Proceedings AAAI Conference, AAAI, August 1982, p. 284

  16. Kelly, V.E., “The CRITTER System: Automated Critiquing of Digital Circuit Designs,”Proceedings of the 21st Design Automation Conference, IEEE, 1984, pp. 419–425

  17. Keuneke, A.M.,Machine Understanding of Devices: Causal Explanation of Diagnostic Conclusions, Ph.D. dissertation, The Ohio State University, Department of Computer and Information Science, 1989

  18. Mackworth, A.K., “Consistency in Networks of Relations,”Artificial Intelligence, Vol. 8, No. 1, 1977, pp. 99–118

    Google Scholar 

  19. Marcus, S., J. McDermott and T. Wang, “Knowledge Acquisition for Constructive Systems,”Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI, 1985, pp. 637–639

  20. McDermott, D.V., “Flexibility and Efficiency in a Computer Program for Designing Circuits,” AI-TR 402, MIT, June 1977

  21. McDermott, J., “R1: an Expert in the Computer Systems Domain,”Proceedings of the 1st Annual National Conference on AI, AAAI, 1980, pp. 269–271

  22. Miller, G.A., E. Galanter and K.H. Pribram,Plans and the Structure of Behavior, Holt, Rinchart and Winston, 1960

  23. Mitchell, T.M., L. Steinberg and J. Shulman, “A Knowledge-Based Approach to Design,”IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. PAMI-7, No. 5, 1985, pp. 502–510

    Google Scholar 

  24. Mittal, S., C. Dym and M. Morjaria, “PRIDE: An Expert System for the Design of Paper Handling Systems,”IEEE Computer, Vol. 19, No. 7, 1986, pp. 102–114

    Google Scholar 

  25. Mittal, S. and F. Frayman, “Towards a Generic Model of Configuration Tasks,”Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit, Michigan, 1989, to appear

  26. Newell, A., “Reasoning, Problem Solving and Decision Process: The Problem Space as a Fundamental Category,”Attention and Performance, VIII, Lawrence Erlbaum, 1980, pp. 693–718

  27. Newell, A., J. E. Laird and P. S. Rosenbloom, “SOAR: An Architecture for General Intelligence,”Artificial Intelligence, Vol. 33, 1987, pp. 1–64

    Google Scholar 

  28. Rich, C., “A Formal Representation for Plans in the Programmer's Apprentice,”Proceedings of the 7th International Joint Conference on Artificial Intelligence, IJCAI, Vancouver, B.C., Canada, August 1981, pp. 1044–1052

    Google Scholar 

  29. Sacerdoti, E.D., “A Structure for Plans and Behavior,” Technical Report 109, AI Center, SRI, Menlo Park, California, 1975

    Google Scholar 

  30. Schank, R.C. and R. Abelson,Scripts, Plans, Goals and Understanding, Lawrence Erlbaum, 1977

  31. Stallman, R. and G. Sussman, “Forward Reasoning and Dependency-Directed Backtracking in a System for Computer-Aided Circuit Analysis,”Artificial Intelligence, Vol. 9, 1977, pp. 135–196; also in MIT AI Lab memo. 380, 1976

    Google Scholar 

  32. Stefik, M., “Planning with Constraints,”Artificial Intelligence, Vol. 16, 1981, pp. 111–140

    Google Scholar 

  33. Sussman, G.J., “A Computational Model of Skill Acquisition,” AI-TR 297, MIT, 1973, Ph.D. dissertation; also in book, same title, Elsevier, 1975

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  1. Laboratory for AI Research, Department of Computer and Information Science, The Ohio State University, Columbus, Ohio, USA

    B. Chandrasekaran

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  1. B. Chandrasekaran
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Chandrasekaran, B. A framework for design problem-solving. Research in Engineering Design 1, 75–86 (1989). https://doi.org/10.1007/BF01580202

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