Solving NP-Complete problems by spiking neural p systems with budding rules

Authors:
Tseren-Onolt Ishdorj;Alberto Leporati;Linqiang Pan;Jun Wang
Affiliations:
Department of Information Technologies, Computational Biomodelling Laboratory, Åbo Akademi University, Turku, Finland;Dipartimento di Informatica, Sistemistica e Comunicazione, Università degli Studi di Milano – Bicocca, Milano, Italy;Key Laboratory of Image Processing and Intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, Hubei, People's Republic of China;Key Laboratory of Image Processing and Intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, Hubei, People's Republic of China
Venue:
WMC'09 Proceedings of the 10th international conference on Membrane Computing
Year:
2009

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Abstract

Inspired by the growth of dendritic trees in biological neurons, we introduce spiking neural P systems with budding rules. By applying these rules in a maximally parallel way, a spiking neural P system can exponentially increase the size of its synapse graph in a polynomial number of computation steps. Such a possibility can be exploited to efficiently solve computationally difficult problems in deterministic polynomial time, as it is shown in this paper for the NP-complete decision problem sat.