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.
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Acknowledgements
F.G.C. Cabarle is grateful for the support of the HRIDD HRDP grant I-15-0626-06 of the DOST PCIEERD, Philippines. N. H. S. Hernandez is supported by the UPAA San Francisco & Mely & Rick Ray foundation professorial chair, and the HRIDD HRDP grant I-15-1006-19 of the DOST PCIEERD, Philippines. M.A. Martínez-del-Amor acknowledges the support of the Alain Bensoussan Fellowship programme of ERCIM, and of the project TIN2012-37434 of the “Ministerio de Economía y Competitividad” of Spain, co-financed by FEDER funds.
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Cabarle, F.G.C., Hernandez, N.H.S., Martínez-del-Amor, M.Á. (2015). Spiking Neural P Systems with Structural Plasticity: Attacking the Subset Sum Problem. In: Rozenberg, G., Salomaa, A., Sempere, J., Zandron, C. (eds) Membrane Computing. CMC 2015. Lecture Notes in Computer Science(), vol 9504. Springer, Cham. https://doi.org/10.1007/978-3-319-28475-0_8
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DOI: https://doi.org/10.1007/978-3-319-28475-0_8
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