Implementation of a NEP in Java

TheNetworks of Evolutionary Processors (NEPs) are computing mechanisms directly inspired from the behavior of cell populations more specifically the point mutations in DNA strands.These mechanisms are been used for solving NP-complete problems by means of a parallel computation postulation.This paper describes an implementation of the basic model of NEP and includes the possibility of designing some of the most common variants of it by means of a graphic user interface which eases the configuration of a given problem. It is a system designed to be used in a multicore processor in order to benefit from the multi thread use

A Web Implementation of A Generalized NEP

The Networks of Evolutionary Processors (NEPs) are computing mechanisms directly inspired from the behavior of cell populations more specifically the point mutations in DNA strands. These mechanisms are been used for solving NP-complete problems by means of a parallel computation postulation. This paper describes an implementation of the basic model of NEP using Web technologies and includes the possibility of designing some of the most common variants of it by means the use of the web page design which eases the configuration of a given problem. It is a system intended to be used in a multicore processor in order to benefit from the multi thread use

Networks of picture processors

Abstract The goal of this work is to survey in a systematic and uniform way the main results regarding different computational aspects of networks of picture processors viewed as rectangular picture accepting devices. We first consider networks with evolutionary picture processors only and discuss their computational power as well as a partial solution to the picture matching problem. Two variants of these networks, which are differentiated by the protocol of communication, are also surveyed: networks with filtered connections and networks with polarized processors. Then we consider networks having both types of processors, i.e., evolutionary processors and hiding processors, and provide a complete solution to the picture matching problem. Several results which follow from this solution are then presented. Finally we discuss some possible directions for further research

Complexity-preserving simulations among three variants of accepting networks of evolutionary processors

In this paper we consider three variants of accepting networks of evolutionary processors. It is known that two of them are equivalent to Turing machines. We propose here a direct simulation of one device by the other. Each computational step in one model is simulated in a constant number of computational steps in the other one while a translation via Turing machines squares the time complexity. We also discuss the possibility of constructing simulations that preserve not only complexity, but also the shape of the simulated network. © 2011 Springer Science+Business Media B.V.This work was supported by the Academy of Finland, projects 132727, 122426, and 108421. F. Manea acknowledges the support from the Alexander von Humboldt Foundation. J Sempere acknowledges the support from the Spanish Ministerio de Educacion y Ciencia project TIN2007-60769.Bottoni ., P.; Labella ., A.; Manea ., F.; Mitrana, V.; Petre ., I.; Sempere Luna, JM. (2011). Complexity-preserving simulations among three variants of accepting networks of evolutionary processors. Natural Computing. 10(1):429-445. https://doi.org/10.1007/s11047-010-9238-5S429445101Alhazov A, Bel Enguix G, Rogozhin Y (2009a) Obligatory hybridnetworks of evolutionary processors. In: International conference on agents and artificial intelligence (ICAART 2009), pp 613–618Alhazov A, Csuhaj-Varj E, Martn-Vide C, Rogozhin Y (2009b) On the size of computationally complete hybrid networks ofevolutionaryprocessors. Theor Comput Sci 410:3188–3197Bottoni P, Labella A, Manea F, Mitrana V, Sempere J (2009a) Filter position in networks of evolutionary processors does not matter: a direct proof. In: Proc. 15th international meeting on DNA computing and molecular programming. 8–11 June 2009, Fayetteville, ArkansasBottoni P, Labella A, Mitrana V, Sempere JM (2009b) Networks of evolutionary picture processors with filtered connections. In: Unconventional computation, 8th international conference (UC 2009), LNCS, vol 5715. Springer, Heidelberg, pp 70–84Castellanos J, Martín-Vide C, Mitrana V, Sempere J (2001) Solving NP-complete problems with networks of evolutionary processors. In: International work-conference on artificial and natural neural networks (IWANN 2001), Lecture notes in computer science, vol 2084, pp 621–628Csuhaj-Varjú E, Mitrana V (2000) Evolutionary systems: a language generating device inspired by evolving communities of cells. Acta Inform 36:913–926Csuhaj-Varjú E, Salomaa A (1997) Networks of parallel language processors. In: New trends in formal languages, Lecture notes in computer science, vol 1218, pp 299–318Dassow J, Truthe B (2007) On the power of networks of evolutionary processors. In: Machines, computations, and universality (MCU 2007), Lecture notes in computer science, vol 4667, pp 158–169Drăgoi C, Manea F (2008) On the descriptional complexity of accepting networks of evolutionary processors with filtered connections. Int J Found Comput Sci 19:1113–1132Drăgoi C, Manea F, Mitrana V (2007) Accepting networks of evolutionary processors with filtered connections. J Univers Comput Sci 13:1598–1614Errico L, Jesshope C (1994) Towards a new architecture for symbolic processing. In: Artificial intelligence and information-control systems of robots ’94, World Scientific, Singapore, pp 31–40Fahlman SE, Hinton GE, Seijnowski TJ (1983) Massively parallel architectures for AI: NETL, THISTLE and Boltzmann machines. In: Proc. of the national conference on artificial intelligence, pp 109–113Hillis W (1985) The connection machine. MIT Press, CambridgeManea F, Martin-Vide C, Mitrana V (2007) On the size complexity of universal accepting hybrid networks of evolutionary processors. Math Struct Comput Sci 17:753–771Margenstern M, Mitrana V, Perez-Jimenez M (2005) Accepting hybrid networks of evolutionary systems. In: DNA based computers 10, Lecture notes in computer science, vol, pp 235–246Martín-Vide C, Mitrana V (2005) Networks of evolutionary processors: results and perspectives. In: Molecular computational models: unconventional approaches. dea Group Publishing, Hershey, pp 78–114Păun G (2000) Computing with membranes. J Comput Syst Sci 61:108–143Păun G, Sântean L (1989) Parallel communicating grammar systems: the regular case. Ann Univ Bucharest Ser Matematica Inform 38:55–63Rozenberg G, Salomaa A (eds) (1997) Handbook of formal languages. Springer–Verlag, BerlinSankoff D et al. (1992) Gene order comparisons for phylogenetic inference: evolution of the mitochondrial genome. Proc Natl Acad Sci USA 89:6575–657