Revistes Publicacions URV: Triangle - llenguatge, literatura, computació> 2012

Developing Tools for Networks of Processors

  • Dades identificatives

    Identificador:  RP:4416
    Handle:  https://hdl.handle.net/20.500.11797/RP4416
    Autors:  Rojas Siles, José Miguel; Cuéllar, Miguel; Anguiano Rey, Eloy; De Lara, Juan; Jiménez Martínez, Antonio; Navarrete Navarrete, Carmen; Del Rosal, Emilio; De la Cruz Echeandía, Marina; Ortega de la Puente, Alfonso
    Resum:
    A great deal of research eort is currently being made in the realm of so called natural computing. Natural computing mainly focuses on the denition, formal description, analysis, simulation and programming of new models of computation (usually with the same expressive power as Turing Machines) inspired by Nature, which makes them particularly suitable for the simulation of complex systems. Some of the best known natural computers are Lindenmayer systems (Lsystems, a kind of grammar with parallel derivation), cellular automata, DNA computing, genetic and evolutionary algorithms, multi agent systems, arti- cial neural networks, P-systems (computation inspired by membranes) and NEPs (or networks of evolutionary processors). This chapter is devoted to this last model.

  • Altres:

    Autor segons l'article: Rojas Siles, José Miguel; Cuéllar, Miguel; Anguiano Rey, Eloy; De Lara, Juan; Jiménez Martínez, Antonio; Navarrete Navarrete, Carmen; Del Rosal, Emilio; De la Cruz Echeandía, Marina; Ortega de la Puente, Alfonso
    Paraules clau: language
    Resum: A great deal of research eort is currently being made in the realm of so called natural computing. Natural computing mainly focuses on the denition, formal description, analysis, simulation and programming of new models of computation (usually with the same expressive power as Turing Machines) inspired by Nature, which makes them particularly suitable for the simulation of complex systems. Some of the best known natural computers are Lindenmayer systems (Lsystems, a kind of grammar with parallel derivation), cellular automata, DNA computing, genetic and evolutionary algorithms, multi agent systems, arti- cial neural networks, P-systems (computation inspired by membranes) and NEPs (or networks of evolutionary processors). This chapter is devoted to this last model.
    Any de publicació de la revista: 2012
    Tipus de publicació: info:eu-repo/semantics/publishedVersion; info:eu-repo/semantics/article