Abstract
In recent years, several researchers have studied the suitability of CBR to cope with dynamic or continuous or temporal domains. In these domains, the current state depends on the past temporal states. This feature really makes difficult to cope with these domains. This means that classical individual case retrieval is not very accurate, as the dynamic domain is structured in a temporally related stream of cases rather than in single cases. The CBR system solutions should also be dynamic and continuous, and temporal dependencies among cases should be taken into account. This paper proposes a new approach and a new framework to develop temporal CBR systems: Episode-Based Reasoning. It is based on the abstraction of temporal sequences of cases, which are named as episodes. Our preliminary evaluation in the wastewater treatment plants domain shows that Episode-Based Reasoning seems to outperform classical CBR systems.
The partial support of TIN2004-01368 and DPI2003-09392-C02-01 Spanish projects and IST-2004-002307 European project are acknowledged.
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References
van Benthem, J.: The Logic of Time. Kluwer Academic, Dordrecht (1983)
Allen, J., Ferguson, G.: Actions and Events in Interval Temporal Logic. The Journal of Logic and Computation 4(5), 531–579 (1994)
Allen, J.: Towards a General Theory of Action and Time. Artificial Intelligence 23, 123–154 (1984)
Allen, J.: Maintaining knowledge about temporal intervals. Communications of the ACM 26(11), 832–843 (1983)
Ma, J., Knight, B.: Reified Temporal logic: An Overview. Artificial Intelligence Review 15, 189–217 (2001)
Ma, J., Knight, B.: A General Temporal Theory. The Computer Journal 37(2), 114–123 (1994)
Shoham, Y.: Temporal Logics in AI: Semantical and Ontological Considerations. Artificial Intelligence 33, 89–104 (1987)
Shanahan, M.A.: Circumscriptive Calculus of Events. Artificial Intelligence 77(2), 249–384 (1995)
Ma, J., Knight, B.: A Framework for Historical Case-Based Reasoning. In: Ashley, K.D., Bridge, D.G. (eds.) ICCBR 2003. LNCS, vol. 2689, pp. 246–260. Springer, Heidelberg (2003)
Jaczynski, M.: A Framework for the Management of Past Experiences with Time-Extended Situations. In: Proc. of the 6th Int. Conference on Information and Knowledge Management (CIKM 1997), Las Vegas, Nevada, USA, November 1997, pp. 32–39 (1997)
Nakhaeizadeh, G.: Learning Prediction of Time Series: A Theoretical and Empirical Comparison of CBR with Some Other Approaches. In: Proceedings of the Workshop on Case-Based Reasoning, AAAI 1994, Seattle, Washington, pp. 67–71 (1994)
Jaere, M., Aamodt, A., Shalle, P.: Representing Temporal Knowledge for Case-Based Reasoning. In: Craw, S., Preece, A.D. (eds.) ECCBR 2002. LNCS (LNAI), vol. 2416, pp. 174–188. Springer, Heidelberg (2002)
Likhachev, M., Kaess, M., Arkin, R.C.: Learning Behavioral Parameterization Using Spatio-Temporal Case-Based Reasoning. In: Proc. of IEEE Int. Conference on Robotics and Automation, ICRA 2002 (2002)
Rosenstein, M.T., Cohen, P.R.: Continuous Categories for a Mobile Robot. In: IJCAI 1999 Workshop on Sequence Learning, pp. 47–53 (1999)
Ram, A., Santamaría, J.C.: Continuous Case-Based Reasoning. Artificial Intelligence 90, 25–77 (1997)
Sànchez-Marrè, M., Cortés, U., Roda, I.R., Poch, M.: Sustainable case learning for continuous domains. Environmental Modelling & Software 14, 349–357 (1999)
Sànchez-Marrè, M., Cortés, U., Roda, I.R., Poch, M.: Using Meta-cases to Improve Accuracy in Hierarchical Case Retrieval. Computación y Sistemas 4(1), 53–63 (2000)
Núñez, H., Sànchez-Marrè, M., Cortés, U.: Improving Similarity Assessment with Entropy-Based Local Weighting. In: Ashley, K.D., Bridge, D.G. (eds.) ICCBR 2003. LNCS (LNAI), vol. 2689, pp. 377–391. Springer, Heidelberg (2003)
Wiese, J., Stahl, A., Hansen, J.: Possible Applications for Case-Based Reasoning in the Field of Wastewater Treatment. In: Proc. of 4th ECAI Workshop on Binding Environmental Sciences and Artificial Intelligence (BESAI 2004), pp. 10-1:10-10 (2004)
Roda, I.R., Sànchez-Marrè, M., Comas, J., Cortés, U., Poch, M.: Development of a case-based system for the supervision of an activated sludge process. Environmental Technology 22(4), 477–486 (2001)
Kraslawski, A., Koiranen, T., Nystrom, L.: Case-Based Reasoning System for Mixing Equipment Selection. Computers & Chemical Engineering 19, 821–826 (1995)
Martínez, M., Sànchez-Marrè, M., Comas, J., Rodríguez-Roda, I.: Case-Based Reasoning, a promising tool to face solids separation problems in the activated sludge process. Water Science & Technology (2005) (in press)
Martínez, M., Mérida-Campos, C., Sànchez-Marrè, M., Comas, J., Rodríguez-Roda, I.: Improving the efficiency of Case-Based Reasoning to deal with activated sludge solids separation problems. Submitted to Environmental Technology (2005)
Rodríguez-Roda, I., Sànchez-Marrè, M., Comas, J., Baeza, J., Colprim, J., Lafuente, J., Cortés, U., Poch, M.: A Hybrid Supervisory System to Support Wastewater Treatment Plant Operation. Water Science & Technology 45(4-5), 289 (2002)
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Sánchez-Marré, M., Cortés, U., Martínez, M., Comas, J., Rodríguez-Roda, I. (2005). An Approach for Temporal Case-Based Reasoning: Episode-Based Reasoning. In: Muñoz-Ávila, H., Ricci, F. (eds) Case-Based Reasoning Research and Development. ICCBR 2005. Lecture Notes in Computer Science(), vol 3620. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11536406_36
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DOI: https://doi.org/10.1007/11536406_36
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