Removing redundancies in constraint networks

  • Authors:

  • Avi Dechter;Rina Dechter

  • Affiliations:

  • Department of Management Science, California State University, Northridge, CA and Cognitive Systems Laboratory, Computer Science Department, University of California, Los Angeles, CA;Artificial Intelligence Center, Hughes Research Laboratories, Calabasas, CA and Cognitive Systems Laboratory, Computer Science Department, University of California, Los Angeles, CA

  • Venue:
  • AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 1
  • Year:
  • 1987

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Abstract

The removal of inconsistencies from the problem's representation, which has been emphasized as a means of improving the performance of backtracking algorithms in solving consttaint satisfaction problems, increases the amount of redundancy in the problem. In this paper we argue that some solution methods might actually benefit from using an opposing strategy, namely, the removal of redundancies from the representation. We present various ways in which redundancies may be identified. In particular, we show how the path-consistency method. developed for removing inconsistencies can be reversed for the purpose of identifying redundancies, and discuss the ways in which redundancy removal can be beneficial in solving consttaint satisfaction problems.