Abstract
Case adaptation, a central component of case-based reasoning, is often considered to be the most difficult part of a case-based reasoning system. The difficulties arise from the fact that adaptation often does not converge, especially if it is not done in a systematic way. This problem, sometimes termed the assimilation problem, is especially pronounced in the case-based design problem solving domain where a large set of constraints and features are processed. Furthermore, in the design domain, multiple cases must be considered in conjunction in order to solve the new problem, resulting in the difficulty of how to efficiently combine the cases into a global solution for the new problem.
In order to achieve case combination, we investigate a methodology which formalizes the process using constraint satisfaction techniques. We represent each case as a primitive constraint satisfaction problem (CSP) and apply an existing repair-based CSP algorithm to combine these primitive CSPs into a globally consistent solution for the new problem. The run time is satisfactory for providing a quick and explicable answer to whether existing cases can be adapted or if new cases would have to be created.
We have tested our methodology in the configuration design and assembly sequence generation domains.
This research is sponsored by the National Science Foundation grant IRI-9208429.
Preview
Unable to display preview. Download preview PDF.
References
W. Bain. Judge. In R.C. Reisbeck, C.K.and Schank, editor, Inside Case-Based Reasoning. Erlbaum Publishers, 1989.
C. Bessiere. Arc consistency in dynamic constraint satisfaction problems. In Proceedings of the 9th Nat. Conf. of AAAI, Anaheim, 1991.
J.G. Carbonell. Derivational analogy: A theory of reconstructive problem solving and expertise acquisition. In Machine Learning, volume 1, 1986.
J.G. Carbonell and M.M. Veloso. Integrating derivational analogy into a general problem solving architecture. In Proceedings: Workshop on Case Based Reasoning (DARPA) Clearwater, Florida. Morgan Kaufmann Publishers, 1988.
Eric Domeshek and Janet Kolodner. Finding the points of large cases. Artificial Intelligence in Engineering Design, Analysis and Manufacturing (AI EDAM), 1993.
W. Ewers. Sincere's Vacuum Cleaner and Small Appliance Repair Service Manual. Sincere Press, 1973.
B. Faltings, D. Haroud, and I. Smith. Dynamic constraint satisfaction with continuous variables. In Proceedings of the European Conf. on AI, Wien, 1992.
D. Gentner. Structure mapping: A theoretical framework for analogy. Cognitive Science, 7, 1983.
K. Hammond. Chef: A model of case-based planning. In Proceedings of AAAI-86, Cambridge, MA, 1986.
D.H. Hennessy and D. Hinkle. Applying case-based reasoning to autoclave loading. IEEE Expert, 7:21–26, 1992.
T.R. Hinrichs. Problem solving in Open Worlds: A case study in Design. Northvale Publishers, 1992.
Kefeng Hua and Boi Faltings. Exploring case-based building design — cadre. Artificial Intelligence in Engineering Design, Analysis and Manufacturing (AI EDAM), 1993.
J. Kolodner. Case Based Reasoning. Morgan Kaufmann Publishers, 1993.
P. Koton. Reasoning about evidence in causal explanation. In Proceedings of AAAI-88, Cambridge, MA, 1988.
Mary Lou Maher and Dong Mei Zhang. Cadsyn: A case-based design process model. Artificial Intelligence in Engineering Design, Analysis and Manufacturing (AI EDAM), 1993.
S. Minton, M. Johnston, A. Philips, and P. Laird. Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems. Artificial Intelligence, 58:161–205, 1992.
S. Mittal and B. Falkenhainer. Dynamic constraint satisfaction. In Proceedings of the 8th National Conference of AAAI, 1990.
Pearl Pu. Issues in case-based design systems. Artificial Intelligence in Engineering Design, Analysis and Manufacturing (AI EDAM), pages 79–85, 1993. As guest editor for a special issue on case-based design systems.
Pearl Pu and Lisa Purvis. Formalizing case adaptation in a case-based design system. In Proceedings of the Third International Conference on Artificial Intelligence in Design (AID94), August 1994.
Pearl Pu and Markus Reschberger. Case-based assembly planning. In Proceedings of DARPA's Case-based Reasoning Workshop. Morgan Kaufmann, 1991.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1995 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Purvis, L., Pu, P. (1995). Adaptation using constraint satisfaction techniques. In: Veloso, M., Aamodt, A. (eds) Case-Based Reasoning Research and Development. ICCBR 1995. Lecture Notes in Computer Science, vol 1010. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60598-3_26
Download citation
DOI: https://doi.org/10.1007/3-540-60598-3_26
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-60598-0
Online ISBN: 978-3-540-48446-2
eBook Packages: Springer Book Archive