Abstract
The development of industrial case-based reasoning systems that have to operate within a continually evolving environment, is a challenging problem. Industrial applications require of robust and competent systems. When the problem domain is evolving, the solutions provided by the system can easily become wrong. In this paper we present an algorithm for dealing with real-world domains where case solutions are evolving along the time. Specifically, the algorithm deals with what we call the innovation problem: the continuous improvements on the components that are part of case solutions. We will show how the use of the proposed algorithm improves significantly the quality of solutions in a deployed engineering design system.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Aamodt, A.: A computational model of knowledge-intensive learning and problem solving. In: Wielinga, B., et al. (eds.) Current Trends in Knowledge Acquisition, IOS Press, Amsterdam (1990)
Aamodt, A.: Knowledge-intensive case-based reasoning and sustained learning. In: Aiello, L. (ed.) Proceedings of the 9th European Conference on Artificial Intelligence, pp. 1–6. Pitman Publishing (1990)
Aamodt, A., Plaza, E.: Case-based reasoning: Foundational issues, methodological variations, and system approaches. Artificial Intelligence Communications 7(1), 39–59 (1994), online at http://www.iiia.csic.es/People/enric/AICom_ToC.html
Arcos, J.-L.: T-air: A case-based reasoning system for designing chemical absorption plants. In: Aha, D.W., Watson, I. (eds.) ICCBR 2001. LNCS (LNAI), vol. 2080, pp. 576–588. Springer, Heidelberg (2001)
Arcos, J.L., de Mántaras, R.L.: Perspectives: a declarative bias mechanism for case retrieval. In: Leake, D.B., Plaza, E. (eds.) ICCBR 1997. LNCS (LNAI), vol. 1266, pp. 279–290. Springer, Heidelberg (1997)
Leake, D.B., Wilson, D.C.: Combining cbr with interactive knowledge acquisition, manipulation and reuse. In: Althoff, K.-D., Bergmann, R., Branting, L.K. (eds.) ICCBR 1999. LNCS (LNAI), vol. 1650, pp. 218–232. Springer, Heidelberg (1999)
Plaza, E., Arcos, J.-L.: Constructive adaptation. In: Craw, S., Preece, A.D. (eds.) ECCBR 2002. LNCS (LNAI), vol. 2416, pp. 306–320. Springer, Heidelberg (2002)
Reinartz, T., Iglezakis, I., Roth-Berghofer, T.: Review and restore for case-based maintenance. Computational Intelligence 17(2), 214–234 (2001)
Richter, M.M.: Introduction. In: Lenz, M., Bartsch-Spörl, B., Burkhard, H.D., Wess, S. (eds.) CBR Technology: From Foundations to Applications, pp. 1–15. Springer, Heidelberg (1998)
Smyth, B., McKenna, E.: Competence models and the maintenance problem. Computational Intelligence 17(2), 235–249 (2001)
Wilson, D.C., Leake, D.B.: Maintaining case-based reasoners: Dimensions and directions. Computational Intelligence 17(2), 196–213 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Arcos, J.L. (2004). Improving the Quality of Solutions in Domain Evolving Environments. In: Funk, P., González Calero, P.A. (eds) Advances in Case-Based Reasoning. ECCBR 2004. Lecture Notes in Computer Science(), vol 3155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28631-8_34
Download citation
DOI: https://doi.org/10.1007/978-3-540-28631-8_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22882-0
Online ISBN: 978-3-540-28631-8
eBook Packages: Springer Book Archive