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Evolving by Maximizing the Number of Rules: Complexity Study

  • Oana Agrigoroaiei
  • Gabriel Ciobanu
  • Andreas Resios
Conference paper
  • 377 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5957)

Abstract

This paper presents the complexity of finding a multiset of rules in a P system in such a way to have a maximal number of rules applied. It is proved that the decision version of this problem is NP-complete. We study a number of subproblems obtained by considering that a rule can be applied at most once, and by considering the number of objects in the alphabet of the membrane as being fixed. When considering P systems with simple rules, the corresponding decision problem is in P. When considering P systems having only two types of objects, and P systems in which a rule is applied at most once, their corresponding decision problems are NP-complete. We compare these results with those obtained for maxO evolution.

Keywords

Decision Problem Turing Machine Knapsack Problem Simple Rule Conjunctive Normal Form 
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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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Oana Agrigoroaiei
    • 1
  • Gabriel Ciobanu
    • 1
  • Andreas Resios
    • 1
  1. 1.Romanian Academy, Institute of Computer Science, Blvd. Carol I no.8, 700505 Iaşi, Romania“A.I.Cuza” UniversityIaşiRomania

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