Details on a public colloquium with the title ``A Class of Computing Models Inspired by Spiking Neurons: A Public Colloquium on Spiking Neural P Systems'' by F. Cabarle

A Class of Computing Models Inspired by Spiking Neurons:

A Public Colloquium on Spiking Neural P Systems

by Francis George C. Cabarle

Algorithms and Complexity Lab

Department of Computer Science

University of the Philippines Diliman


Spiking neural P systems (in short, SNP systems) are a class of parallel, distributed, and nondeterministic models of computation. SNP systems are membrane models within the larger membrane computing area (which is further included into natural computing) initiated by Gheorghe Paun in 1998. In what follows, we mention briefly some of the topics that will be touched in this colloquium. Membrane computing is a systematic assault on computations inspired by the living cell, continuing the goal of natural computing of obtaining computing ideas from (or even performing computations in) the natural world. In the case of SNP systems, the inspiration mainly comes from a specific cell called a neuron. Neurons are placed on the nodes of a directed graph with synapses as arcs between neurons. The spiking of a neuron using a spiking rule produces a signal simply called the spike. The spiking neuron uses time not only as a background for information, but as information support also: e.g. a number n can be encoded as the time interval between the times t' – t = n, t' > t, of spike production of a neuron. This idea of using time as support produced a menagerie of ways to introduce inputs or extract outputs, which gave rise to many SNP system variants. Other SNP system variants include other neuroscience ideas, which are then used for computing purposes, e.g. astrocytes or glial cells, neural stem cell division. The issues of computability (how powerful a computing model is) and computational efficiency (how much time and space is required for computations) are given: SNP systems and their many variants are known to be Turing universal (i.e. they can simulate a universal Turing machine) and computationally efficient (i.e. they can efficiently solve NP-complete problems). The colloquium aims to provide an introduction on these computing issues (both closed and open) for the interested viewers and researchers in fields related to computing.

Keywords: Natural Computing, Membrane Computing, Spiking Neural P systems, Models of computation, Turing universality

Date: 23 April 2015, Thursday

Time: 16:30 – 18:00

Venue: ERDT room, Department of Computer Science,

Velasquez St., UP Diliman, Quezon city

Faculty, students, and the general public are invited.

The abstract poster is attached as a PDF file in this page.

The slides are attached as a PDF file in this page.