A tutorial on the formal framework for spiking neural P systems

The model of Spiking Neural P systems (SNP systems) is a widespread computational model in the area of membrane computing. It has numerous applications, especially related to machine learning. Most of these applications require a custom variant of SNP systems, differing by the rule form and by semantics. The model of network of cells and the formal framework for SNP systems were developed to help the analysis of such custom models, to compare and relate them to each other and to other models of computing. The model specifies the data structure, the rules and the update procedure, while the formal framework concentrates on how the input, output and the choice of the update strategy are handled. Together, these concepts specify a concrete instance of a network of cells that strongly bisimulates the desired model, thus making easier the process of the creation of new models and the extension of existing ones. Since the formal framework is rather generic, it might be slightly complex to use it for concrete cases. This paper provides a tutorial that explains the model of networks of cells and the basic concepts used in the formal framework for SNP systems. It gives a series of examples for the analysis of existing models, their bisimulation and their extension by different features.