International Conference on Membrane Computing

Membrane Computing pp 106-116 | Cite as

Spiking Neural P Systems with Structural Plasticity: Attacking the Subset Sum Problem

  • Francis George C. Cabarle
  • Nestine Hope S. Hernandez
  • Miguel Ángel Martínez-del-Amor
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9504)

Abstract

Spiking neural P systems with structural plasticity (in short, SNPSP systems) are models of computations inspired by the function and structure of biological neurons. In SNPSP systems, neurons can create or delete synapses using plasticity rules. We report two families of solutions: a non-uniform and a uniform one, to the NP-complete problem \(\mathtt {Subset~Sum}\) using SNPSP systems. Instead of the usual rule-level nondeterminism (choosing which rule to apply) we use synapse-level nondeterminism (choosing which synapses to create or delete). The nondeterminism due to plasticity rules have the following improvements from a previous solution: in our non-uniform solution, plasticity rules allowed for a normal form to be used (i.e. without forgetting rules or rules with delays, system is simple, only synapse-level nondeterminism); in our uniform solution the number of neurons and the computation steps are reduced.

Keywords

Membrane computing Spiking neural P system Structural plasticity NP-complete Subset Sum 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Francis George C. Cabarle
    • 1
  • Nestine Hope S. Hernandez
    • 1
  • Miguel Ángel Martínez-del-Amor
    • 2
  1. 1.Algorithms and Complexity Lab, Department of Computer ScienceUniversity of the Philippines DilimanQuezon CityPhilippines
  2. 2.Department of Computer Science and AIUniversity of SevillaSevillaSpain

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