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ILISCE: A system for learning control heuristics in a scheduling environment

  • Thierry Van de Merckt
Finance
Part of the Lecture Notes in Computer Science book series (LNCS, volume 604)

Abstract

This paper presents a general learning structure called Ilisce which learns meta-rules to guide a scheduling system. The scheduling program, called Opal, solves real-world problems using a set of local heuristics which incrementaly resolve the whole set of conflicts among the physical resources of the floor. A Selective Inductive learning approach is used to create concepts representing typical states of the job shop which allow a Classifier to “recognize” current situations and to choose the corresponding best operators to apply on. In this paper, we present the general architecture of Ilisce.

Keywords

Scheduling Learning Credit Assignment 

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Thierry Van de Merckt
    • 1
  1. 1.IRIDIA, Université Libre de BruxellesBruxellesBelgium

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