Abstract
Cased-Based Reasoning (CBR) is based on the use of previous experiences to solve new problems. In this work, we propose to use CBR paradigm for solving control reconfiguration problems. The reconfiguration task aims to maintain the system working despite some situations that may affect it (faults, change in production strategy, …). The main issue is then to find the new laws or rules to use in each different situation. In this article, we especially focus on the representation part. In fact, representation is a very important task in this type of problematic as the structure of the case will affect all the other phases of the CBR cycle.
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References
Aamodt, A., Plaza, E.: Case-based reasoning: Foundational issues, methodological variations, and system approaches. In: AICom - Artificial Intelligence Communications, vol. 7(1), pp. 39–59 (1994)
Askari-Marnani, J., Heiming, B., Lunze, J.: Control reconfiguration:the cosy benchmark problem and its solution by means of a qualitative model. In: Part of Chapter 21 of the Final Report of the Project ” Control of Complex Systems”, cosy (2001)
Bergmann, R., Muñoz-Ávila, H., Veloso, M.M., Melis, E.: CBR Applied to Planning. In: Lenz, M., Bartsch-Spörl, B., Burkhard, H.-D., Wess, S. (eds.) Case-Based Reasoning Technology. LNCS (LNAI), vol. 1400, pp. 169–199. Springer, Heidelberg (1998)
Göker, M.H., Howlett, R.J., Price, J.E.: Case-based reasoning for diagnosis applications. The Knowledge Engineering Review 20(03), 277–281 (2005)
Kolodner, J.L.: An introduction to case-based reasoning. Artificial Intelligence Review 6(1), 3–34 (1992)
Kolodner, J.L.: Case Based Reasoning. Morgan Kaufmann Publishers Inc. (1993)
Lejri, O., Tagina, M.: Hybrid reconfigurable petri nets for modelling hybrid reconfigurable manufacturing systems. Journal of Studies on Manufacturing 1(2–3), 75–84 (2010)
Lenz, M., Burkhard, H.D., Pirk, P., Auriol, E., Manago, M.: Cbr for diagnosis and decision support. AI Communications - Special Issue on ECAI 1996 Budapest 9(3) (September 1996)
Lunze, J., Askari, J., et al.: Three-tank reconfiguration control. Control of Complex Systems, 241–283 (2001)
Maciejowski, J.: Reconfiguring control systems by optimization. In: European Control Conference, Brussels (1997)
Marques, V., Farinha, J.T., Brito, A.: Cbr for diagnosis: evidence relevance and case adaptation. In: ICCOMP 2009 Proceedings of the WSEAES 13th International Conference on Computers. World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, Wisconsin, USA (2009)
Minsky, M.: A framework for representing knowledge. In: The Psycology of Computer Vision. McGraw-Hill, New York (1975)
Pal, S.K., Shiu, S.C.K.: Foundations of Soft Case-based Reasoning. Wiley series on intelligent systems. Wiley-Interscience publication, A John Wiley & Sons, Inc., New York (2004)
Perner, P., Holt, A., Richter, M.M.: Image processing in case-based reasoning. The Knowledge Engineering Review 20(03), 311–314 (2005)
Schank, R.C.: Dynamic memory, a theory of reminding and learning in computers and people, 1st edn. Cambridge University Press, New York (1982)
Tsuda, K., Mignone, D., Ferrari-Trecate, G., Morari, M.: Reconfiguration strategies for hybrid systems. In: Proceedings of the American Control Conference, Arlington, VA, June 25-27, pp. 868–873 (2001)
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Lejri, O., Tagina, M. (2012). Representation in Case-Based Reasoning Applied to Control Reconfiguration. In: Perner, P. (eds) Advances in Data Mining. Applications and Theoretical Aspects. ICDM 2012. Lecture Notes in Computer Science(), vol 7377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31488-9_10
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DOI: https://doi.org/10.1007/978-3-642-31488-9_10
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