Finding diverse and similar solutions in constraint programming

  • Authors:
  • Emmanuel Hebrard;Brahim Hnich;Barry O'Sullivan;Toby Walsh

  • Affiliations:
  • NICTA and UNSW, Sydney, Australia;University College Cork, Ireland;University College Cork, Ireland;NICTA and UNSW, Sydney, Australia

  • Venue:
  • AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
  • Year:
  • 2005

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Abstract

It is useful in a wide range of situations to find solutions which are diverse (or similar) to each other. We therefore define a number of different classes of diversity and similarity problems. For example, what is the most diverse set of solutions of a constraint satisfaction problem with a given cardinality? We first determine the computational complexity of these problems. We then propose a number of practical solution methods, some of which use global constraints for enforcing diversity (or similarity) between solutions. Empirical evaluation on a number of problems show promising results.