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A return to stochasticity and probability in spiking neural P systems

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Abstract

This work continues the investigations of introducing probabilities to spiking neural P systems, SN P systems in short—membrane computing models inspired from biological spiking neurons. A particular interest for SN P systems in this work is the nondeterministic selection of applicable firing rules. Rules represent the possible reactions of a neuron to the number of electrical impulses, or spikes, present. Intuitively, having nondeterministic selection can be interpreted as having a random choice with equal probabilities for all options. This seems unnatural in some biological sense, since some reactions are more active than others in general as emphasized in Obtułowicz and Păun, BioSystems 70(2):107–121, 2003. Results found that the stochastic process introduced to the nondeterministic selection of firing rules also applies to application of rules in general whether the rule is for firing or forgetting and whether a single rule is applicable or multiple. This work proposes SN P systems with stochastic application of rules, \(\star \)SN P systems in short. \(\star \)SN P systems are variants which introduce a stochastic process a priori to the application of rules in SN P systems.

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Notes

  1. stochastic application of rules

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Acknowledgement

F.G.C. Cabarle thanks the support from the DOST-ERDT project; the Dean Ruben A. Garcia PCA AY2017–2020. H. Adorna would like to thank supports from DOST-ERDT project since 2009 until present; the Semirara Mining Corp. Professorial Chair Award since 2015 until present. The RLC grant from UPD - OVCRD 2019–2020.

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Authors and Affiliations

  1. Algorithms and Complexity, Department of Computer Science, University of the Philippines Diliman, Diliman, 1101, Quezon City, Philippines

    Prometheus Peter L. Lazo, Francis George C. Cabarle, Henry N. Adorna & Jan Michael C. Yap

  2. Philippine Genome Center, University of the Philippines Diliman, Diliman, 1101, Quezon City, Philippines

    Jan Michael C. Yap

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  1. Prometheus Peter L. Lazo
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  2. Francis George C. Cabarle
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  3. Henry N. Adorna
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  4. Jan Michael C. Yap
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Correspondence to Francis George C. Cabarle.

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Appendix

Appendix

Table 1 Summary of surveyed stochastic computing models
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Table 2 A computation in the system from Fig. 4
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Table 3 A computation in the system from Fig. 5
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Table 4 A computation in the system from Fig. 6
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Lazo, P.P.L., Cabarle, F.G.C., Adorna, H.N. et al. A return to stochasticity and probability in spiking neural P systems. J Membr Comput 3, 149–161 (2021). https://doi.org/10.1007/s41965-021-00072-4

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