Significance of models of computation, from Turing model to natural computation
Artikel i vetenskaplig tidskrift, 2011

The increased interactivity and connectivity of computational devices along with the spreading of computational tools and computational thinking across the fields, has changed our understanding of the nature of computing. In the course of this development computing models have been extended from the initial abstract symbol manipulating mechanisms of stand-alone, discrete sequential machines, to the models of natural computing in the physical world, generally concurrent asynchronous processes capable of modelling living systems, their informational structures and dynamics on both symbolic and sub-symbolic information processing levels. Present account of models of computation highlights several topics of importance for the development of new understanding of computing and its role: natural computation and the relationship between the model and physical implementation, interactivity as fundamental for computational modelling of concurrent information processing systems such as living organisms and their networks, and the new developments in logic needed to support this generalized framework. Computing understood as information processing is closely related to natural sciences; it helps us recognize connections between sciences, and provides a unified approach for modeling and simulating of both living and non-living systems. © Springer Science+Business Media B.V. 2011.

Philosophy of computing

Hypercomputing

Models of computation

Philosophy of computer science

Theory of computation

Philosophy of information

Författare

Gordana Dodig Crnkovic

Göteborgs universitet

Chalmers, Tillämpad informationsteknologi

Minds and Machines

0924-6495 (ISSN) 1572-8641 (eISSN)

Vol. 21 301-322

Ämneskategorier

Annan data- och informationsvetenskap

Data- och informationsvetenskap

Filosofi

Datavetenskap (datalogi)

Styrkeområden

Informations- och kommunikationsteknik

Infrastruktur

C3SE (Chalmers Centre for Computational Science and Engineering)

DOI

10.1007/s11023-011-9235-1