A New Characterization of NP, P, and PSPACE with Accepting Hybrid Networks of Evolutionary Processors

We consider three complexity classes defined on Accepting Hybrid Networks of Evolutionary Processors (AHNEP) and compare them with the classical complexity classes defined on the standard computing model of Turing machine. By definition, AHNEPs are deterministic. We prove that the classical complexi...

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Detalles Bibliográficos
Autores: Manea, Florin, Margenstern, Maurice, Mitrana, Víctor, Pérez Jiménez, Mario de Jesús
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2010
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/69142
Acceso en línea:https://hdl.handle.net/11441/69142
https://doi.org/10.1007/s00224-008-9124-z
Access Level:acceso abierto
Palabra clave:Evolution strategies
Evolutionary processor
Network of evolutionary processors
Turing machine
Computational complexity classes
Descripción
Sumario:We consider three complexity classes defined on Accepting Hybrid Networks of Evolutionary Processors (AHNEP) and compare them with the classical complexity classes defined on the standard computing model of Turing machine. By definition, AHNEPs are deterministic. We prove that the classical complexity class NP equals the family of languages decided by AHNEPs in polynomial time. A language is in P if and only if it is decided by an AHNEP in polynomial time and space. We also show that PSPACE equals the family of languages decided by AHNEPs in polynomial length.