Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-10T23:21:00.612Z Has data issue: false hasContentIssue false
  • English
  • Français

A framework for case-based reasoning in engineering design

Published online by Cambridge University Press:  27 February 2009

H. Shiva Kumar  and
C.S. Krishnamoorthy
H. Shiva Kumar
Affiliation:
Department of Civil Engineering, Indian Institute of Technology, Madras, 600 036, India
C.S. Krishnamoorthy
Affiliation:
Department of Civil Engineering, Indian Institute of Technology, Madras, 600 036, India
Get access Rights & Permissions [Opens in a new window]

Abstract

Although the case-based reasoning (CBR) process is domain dependent, certain aspects of it can readily be captured into a generic framework which in turn can be applied to various engineering domains. One such exercise that has been carried out is described here. In this paper, we present the notion that CBR can be formalized and applied in a specialized framework in an integrated knowledge-based environment. We first analyze the CBR process to abstract the steps involved in the development of a CBR system. We then propose a framework in which most of these steps are formalized so that they can be applied in a domain-independent manner. The salient features of this framework, called CASETOOL (CASE-based reasoning TOOL-kit), are then described. The highlight of this approach is the use of a concept called design criticism in the CBR process. The versatility of the tool is demonstrated through an application from the bridge engineering domain.

Keywords

Case-Based ReasoningEngineering DesignKBS Development ToolBridge Design
Type
Articles
Information
AI EDAM , Volume 9 , Issue 3 , June 1995 , pp. 161 - 182
Copyright
Copyright © Cambridge University Press 1995

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Alderman, R. (1986). An adaptive planner. Proc. AAAI-86, 65–69.Google Scholar
Bain, W.M. (1986). A case-based reasoning system for subjective assessment. Proc. National Conf. on AI, 523–527.Google Scholar
Barletta, R. & Mark, W. (1988). Explanation-based indexing of cases. Proc. DARPA Workshop on Case-Based Reasoning, 50–60.Google Scholar
Bardasz, T., & Zeid, I. (1993). DEJAVU: Case-based reasoning for mechanical design. AI EDAM, 7(2), 111–124.Google Scholar
Bergan, P.L., & Clough, R.W. (1978). Convergence criteria for iterative processes. AlAA, 10(8), 1107–1108.Google Scholar
Barting, K.L. (1988). The role of explanation in reasoning from legal precedents. Proc. DARPA Workshop on Case-Based Reasoning, 286–301.Google Scholar
Barting, K.L., & Porter, B.W. (1991). Rules and precedents as complementary warrants. Proc. 9th National Conf. on AI, AAAI, Vol. 1, 3–9.Google Scholar
Breadshaw, G. (1987). Learning about speech sounds: The NEXUS project. Proc. 4th International Workshop on Machine Learning, 1–11.CrossRefGoogle Scholar
Corbonell, J.G. (1983). Learning by analogy: Formulation and generalizing plans from past experience. Machine Learning: An Artificial Intelligence Approach, pp. 137–161. Tioga Publishing Company, Palo Alto, California.Google Scholar
Corbonell, J.G. (1986). Derivational analogy: A theorem of reconstructive problem solving and expertise acquisition. Machine Learning: An Artificial Intelligence Approach, pp. 371–392. Morgan Kaufman Publishers, Inc., Los Altos, California.Google Scholar
Cullingford, R.E., & Kolodner, J.L. (1986). Interactive advice giving. Proc. IEEE International Conf. on Systems, Man and Cybernatics.Google Scholar
Domeshek, E., & Kolodner, J. (1993). Using the points of large cases. AI EDAM, 7(2), 87–96.Google Scholar
Dym, C. L., & Levitt, R. E. (1991). Knowledge-Based Systems in Engineering Design. McGraw-Hill, Inc., New York, USA.Google Scholar
Gero, J. (1990). Design prototypes: A knowledge representation schema for design. AI Magazine, Winter, 26–36.Google Scholar
Goel, A., & Chandrasekaran, B. (1989). Use of device model in adaption of design cases. Proc. of the DARPA Workshop on Case-Based Reasoning, pp. 100–109. Pensacola Beach, Florida, USA.Google Scholar
Goel, A., Kolodner, J., Pearce, M., & Billington, R. (1991). Towards a case-based tool for aiding conceptual design problem solving. Proc. of the DARPA Workshop on Case-Based Reasoning, pp. 109–120. Washington DC, USA.Google Scholar
Hammond, K.J. (1986). CHEF: A model of case-based planning. Proc. AAAI-86, 1, 267–271.Google Scholar
Heins, C.P., & Lawrie, R.A. (1984). Design of Modern Concrete Highway Bridges. John Wiley & Sons, Inc., New York, USA.Google Scholar
Hinrichs, D., & Kolodner, J.L. (1991). The role of adaption in case-based design. Proc. Ninth National Conf. on AI, AAAI-91, July, Vol. 1, pp. 28–33. MIT Press, London.Google Scholar
Howard, C.H., Wang, J., Daube, F., & Rafiq, T. (1989). Applying design-dependent knowledge in structural engineering design. AI EDAM, 3(2), 111–123.Google Scholar
Hua, K., & Faltings, B. (1993). Exploring case-based building design — CADRE. AI EDAM, 7(2), 135–143.Google Scholar
Kolodner, J.L. (1985). Memory for experience. The Psychology of Learning and Motivation (Bower, G., Ed.), Vol. 19. Academic Press, Orlando, Florida.Google Scholar
Kolodner, J.L. (1987). Extending problem solving capabilities through case-based inferences. Proc. Fourth International Workshop on Machine Learning, pp. 167–178. Morgan Kaufmann, Irvine, California.Google Scholar
Kolodner, J.L. (1993). Case-Based Reasoning. Morgan Kaufmann Publishers, Inc., San Mateo, California.Google Scholar
Krishnamoorthy, C.S., Rajeev, S., Karimulla Raja, S., & Shiva Kumar, H. (1991a). Development environment for knowledge based systems in engineering design. Proc. Second Int. Conf. on Appl. of AI Tech. to Civil and Structural Engineering (Topping, B.H.V., Ed.), pp. 165–174. Oxford, England.Google Scholar
Krishnamoorthy, C.S., Srinivasa Rao, C., & Rajeev, S. (1991b). Architecture of an engineering design synthesizer for KBES. Proc. of the Second Int. Conf. on Appl. of AI Tech. to Civil and Structural Engineering, Oxford, England, September, (Topping, B.H.V., Ed.), pp. 79–86. Civil-Comp Press, Edinburgh, England.Google Scholar
Krishnamoorthy, C.S., Shiva Kumar, H., Rajeev, S., & Suresh, S. (1993). Knowledge based system with generic tools for structural engineering design. Structural Engineering Review 5(2), 121–131.Google Scholar
Lehnert, W. (1987). Case-based problem solving with a large knowledge base of learned cases. Proc. National Conf. on AI, 301–306.Google Scholar
Maher, M.L. (1987). Engineering design synthesis: A domain independent implementation. AI EDAM, 1(3), 207–213.Google Scholar
Maher, M.L. (1990). HI-RISE and beyond: Directions for expert systems in design. Computer Aided Design, 17(9), 420–427.Google Scholar
Maher, M.L., & Zhang, D.M. (1991). CADSYN: Using cases and decomposition knowledge for design synthesis. Artificial Intelligence in Design (Gero, J.S., Ed.), pp. 137–150. Butterworth-Heinemann, Oxford.Google Scholar
Maher, M.L., & Zhang, D.M. (1993). CADSYN: A case-based design process model. AI EDAM, 7(2), 97–110.Google Scholar
Navinchandra, D. (1988). Case-based reasoning in CYCLOPS, a design problem solver. Proc. DARPA Workshop on Case-Based Reasoning, 286–301.Google Scholar
Pu, P. (1993). Introduction: Issues on case-based design systems. AI EDAM, 7(2), 79–86.Google Scholar
Riesbeck, C.K., & Schank, R.C. (1989). Inside Case-Based Reasoning. Lawrence Erlbaum, Hillsdale, NJ.Google Scholar
Roderman, S., & Tsatsoulis, C. (1993). PANDA: A case-based system to AI novice designers. AI EDAM, 7(2), 125–133.Google Scholar
Rosenman, M.A., Gero, J.S., & Oxman, R.E. (1992). What's in a case: The use of case-bases, knowledge-bases, and databases in design. CAAD Futures '91, (Schmitt, G.N., Ed.), pp. 285–300. Vieweg, Wiesbaden.Google Scholar
Schank, R.C. (1982). Dynamic Memory: A Theory of Learning in Computers and People. Cambridge University Press, New York.Google Scholar
Schank, R.C. (1986). Explanation Patterns: Understanding Mechanically and Creativity. Lawrence Erlbaum, Hillsdale, NJ.Google Scholar
Shiva Kumar, H., Suresh, S., Krishnamoorthy, C.S., Fenves, S.J., & Rajeev, S. (1994). GENCRIT: A tool for knowledge-based critiquing in engineering design. AI EDAM, 8(3), 239–259.Google Scholar
Simon, H.A. (1973). The structure of ill-structured problems. Artificial Intelligence, 4, 181–201.Google Scholar
Zhang, D.M., & Maher, M.L. (1991). The transformational process in case-based reasoning in design. Proc. IJCAI-12 Workshop on AI in Design (Gero, J.S. & Sudweeks, F., Eds.), pp. 321–336. Sydney, Australia: Department of Architectural and Design Science, University of Sydney.Google Scholar
Zhao, F., & Maher, M.L. (1988). Using analogical reasoning to design buildings. Engineering with Computers, 4, 107–119.CrossRefGoogle Scholar