Blocking and Other Enhancements for Bottom-Up Model Generation Methods

  • Peter Baumgartner
  • Renate A. Schmidt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4130)


In this paper we introduce several new improvements to the bottom-up model generation (BUMG) paradigm. Our techniques are based on non-trivial transformations of first-order problems into a certain implicational form, namely range-restricted clauses. These refine existing transformations to range-restricted form by extending the domain of interpretation with new Skolem terms in a more careful and deliberate way. Our transformations also extend BUMG with a blocking technique for detecting recurrence in models. Blocking is based on a conceptually rather simple encoding together with standard equality theorem proving and redundancy elimination techniques. This provides a general-purpose method for finding small models. The presented techniques are implemented and have been successfully tested with existing theorem provers on the satisfiable problems from the TPTP library.


Theorem Prove Description Logic Automate Reasoning Predicate Symbol Domain Element 
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 2006

Authors and Affiliations

  • Peter Baumgartner
    • 1
  • Renate A. Schmidt
    • 2
  1. 1.National ICT Australia (NICTA) 
  2. 2.The University of Manchester 

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