An approach for temporal case-based reasoning: episode-based reasoning

  • Authors:

  • Miquel Sánchez-Marré;Ulises Cortés;Montse Martínez;Joaquim Comas;Ignasi Rodríguez-Roda

  • Affiliations:

  • Technical University of Catalonia, Knowledge Engineering & Machine Learning Group, Catalonia University of Girona, Barcelona;Technical University of Catalonia, Knowledge Engineering & Machine Learning Group, Catalonia University of Girona, Barcelona;Chemical & Environmental Engineering Laboratory, Girona, Catalonia;Chemical & Environmental Engineering Laboratory, Girona, Catalonia;Chemical & Environmental Engineering Laboratory, Girona, Catalonia

  • Venue:
  • ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
  • Year:
  • 2005

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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.