A Semantic Account for Modularity in Multi-language Modelling of Search Problems

  • Shahab Tasharrofi
  • Eugenia Ternovska
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6989)


Motivated by the need to combine systems and logics, we develop a modular approach to the model expansion (MX) problem, a task which is common in applications such as planning, scheduling, computational biology, formal verification. We develop a modular framework where parts of a modular system can be written in different languages. We start our development from a previous work, ?, but modify and extend that framework significantly. In particular, we use a model-theoretic setting and introduce a feedback (loop) operator on modules. We study the expressive power of our framework and demonstrate that adding the feedback operator increases the expressive power considerably. We prove that, even with individual modules being polytime solvable, the framework is expressive enough to capture all of NP, a property which does not hold without loop. Moreover, we demonstrate that, using monotonicity and anti-monotonicity of modules, one can significantly reduce the search space of a solution to a modular system.


Logic Program Expressive Power Hamiltonian Path Predicate Symbol Modular System 
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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© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Shahab Tasharrofi
    • 1
  • Eugenia Ternovska
    • 1
  1. 1.Simon Fraser UniversityCanada

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