1. A formal framework for spiking neural P systems
- Author
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Sergiu Ivanov, Artiom Alhazov, Sergey Verlan, Rudolf Freund, Linqiang Pan, Laboratoire d'Algorithmique Complexité et Logique (LACL), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Informatique, BioInformatique, Systèmes Complexes (IBISC), and Université d'Évry-Val-d'Essonne (UEVE)-Université Paris-Saclay
- Subjects
Vector addition ,Class (computer programming) ,Current (mathematics) ,Quantitative Biology::Neurons and Cognition ,business.industry ,Computer science ,Applied Mathematics ,Extension (predicate logic) ,[INFO.INFO-FL]Computer Science [cs]/Formal Languages and Automata Theory [cs.FL] ,Computational Theory and Mathematics ,Simple (abstract algebra) ,Theory of computation ,Process information ,Artificial intelligence ,business - Abstract
Spiking neural P systems are a class of distributed parallel computing models, inspired by the way in which neurons process information and communicate with each other by means of spikes. In 2007, Freund and Verlan developed a formal framework for P systems to capture most of the essential features of P systems and to define their functioning in a formal way. In this work, we present an extension of the formal framework related to spiking neural P systems by considering the applicability of each rule to be controlled by specific conditions on the current contents of the cells. The main objective of this extension is to also capture spiking neural P systems in the formal framework. Another goal of our extension is to incorporate the notions of input and output. Finally, we also show that in the case of spiking neural P systems, the rules have a rather simple form and in that way spiking neural P systems correspond to vector addition systems where the application of rules is controlled by semi-linear sets.
- Published
- 2020