A Dynamical Characterization of Case-Based Reasoning Systems for Improving Its Performance in Highly Dynamic Environments

  • Luis F. Castillo
  • M. G. Bedia
  • M. Aguilera
  • L. Uribe
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 91)


In this paper a mathematical technique is presented for modelling the generation of solutions in a standard-CBR methodology adapted to highly dynamic environments. In recent years, much research has focused on exploring how to improve CBR-systems to deal with dynamic environments where changes are difficult to model or predict and, consequently, the performance of the CBRs gets worse with time. High-level planning, reactive strategies or hybrid alternatives have been proposed to face this problem, but this contribution will not be related on particular techniques.We simply concentrate on formal aspects without establishing which should be the most adequate procedure in a subsequent implementation stage. The advantage of the presented scheme is that it does not depend on neither the problem nor the model of the environment. It consists in a formal approach that only requires, local information about the averaged-time spent by the system in obtaining a solution and an estimated measure about the dynamism of the environment.


Dynamic Environment Case Base Reasoning Formal Aspect Greedy Strategy Dynamical Characterization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Luis F. Castillo
    • 1
  • M. G. Bedia
    • 2
  • M. Aguilera
    • 2
  • L. Uribe
    • 3
  1. 1.Industrial engineeringNational University of ColombiaColombia
  2. 2.Computer ScienceUniversity of ZaragozaSpain
  3. 3.Computer ScienceAutonomous University of ManizalesColombia

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