Towards a Meta-model for Natural Computers: An Example Using Metadepth

  • Marina de la Cruz
  • Suzan Awinat
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 156)

Abstract

Model Driven is currently one of the most promising approaches to software engineering. One of the topics related to this area is the possibility of defining models that could also be considered as meta models, that is, that could be instantiated to get a less abstract model. Most of the current tools available allow the definition of two levels: the model that can be instantiated (and hence be considered a meta model) and the specific model we can get after instantiating the first one. Nevertheless some domains require more than two levels. One of them can be found in the realm of the so called natural computers. This domain includes several models that share different characteristics. Each model could be instantiated to define particular cases able to solve specific problems. So we need to define a first level with the common features of all the natural computing models. This first level will be instantiated to get the particular models of natural computing. These models will be finally instantiated to get the specific systems we could use to solve a given task. MetaDepth is one of the first tools that offers the designers the possibility of defining a chain of models of this kind. This paper shows a first step for using MetaDepth in natural computing.

Keywords

Programming Language Turing Machine Abstract Model Natural Computer Natural Computing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Marina de la Cruz
    • 1
  • Suzan Awinat
    • 1
  1. 1.Escuela Politécnica Superior, Departamento de Ingeniería InformáticaUniversiad Autónoma de MadridMadridSpain

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