Evolution and development of complex computational systems using the paradigm of metabolic computing in Epigenetic Tracking

Epigenetic Tracking (ET) is an Artificial Embryology system which allows for the evolution and development of large complex structures built from artificial cells. In terms of the number of cells, the complexity of the bodies generated with ET is comparable with the complexity of biological organism...

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Main Authors: Alessandro Fontana, Borys Wróbel
Format: Article
Language:English
Published: Open Publishing Association 2013-09-01
Series:Electronic Proceedings in Theoretical Computer Science
Online Access:http://arxiv.org/pdf/1309.7688v1
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spelling doaj-fdf491823be54f26a27f7f483eb5ec7f2020-11-24T23:51:22ZengOpen Publishing AssociationElectronic Proceedings in Theoretical Computer Science2075-21802013-09-01130Proc. Wivace 2013273410.4204/EPTCS.130.5Evolution and development of complex computational systems using the paradigm of metabolic computing in Epigenetic TrackingAlessandro FontanaBorys WróbelEpigenetic Tracking (ET) is an Artificial Embryology system which allows for the evolution and development of large complex structures built from artificial cells. In terms of the number of cells, the complexity of the bodies generated with ET is comparable with the complexity of biological organisms. We have previously used ET to simulate the growth of multicellular bodies with arbitrary 3-dimensional shapes which perform computation using the paradigm of ``metabolic computing''. In this paper we investigate the memory capacity of such computational structures and analyse the trade-off between shape and computation. We now plan to build on these foundations to create a biologically-inspired model in which the encoding of the phenotype is efficient (in terms of the compactness of the genome) and evolvable in tasks involving non-trivial computation, robust to damage and capable of self-maintenance and self-repair.http://arxiv.org/pdf/1309.7688v1
collection DOAJ
language English
format Article
sources DOAJ
author Alessandro Fontana
Borys Wróbel
spellingShingle Alessandro Fontana
Borys Wróbel
Evolution and development of complex computational systems using the paradigm of metabolic computing in Epigenetic Tracking
Electronic Proceedings in Theoretical Computer Science
author_facet Alessandro Fontana
Borys Wróbel
author_sort Alessandro Fontana
title Evolution and development of complex computational systems using the paradigm of metabolic computing in Epigenetic Tracking
title_short Evolution and development of complex computational systems using the paradigm of metabolic computing in Epigenetic Tracking
title_full Evolution and development of complex computational systems using the paradigm of metabolic computing in Epigenetic Tracking
title_fullStr Evolution and development of complex computational systems using the paradigm of metabolic computing in Epigenetic Tracking
title_full_unstemmed Evolution and development of complex computational systems using the paradigm of metabolic computing in Epigenetic Tracking
title_sort evolution and development of complex computational systems using the paradigm of metabolic computing in epigenetic tracking
publisher Open Publishing Association
series Electronic Proceedings in Theoretical Computer Science
issn 2075-2180
publishDate 2013-09-01
description Epigenetic Tracking (ET) is an Artificial Embryology system which allows for the evolution and development of large complex structures built from artificial cells. In terms of the number of cells, the complexity of the bodies generated with ET is comparable with the complexity of biological organisms. We have previously used ET to simulate the growth of multicellular bodies with arbitrary 3-dimensional shapes which perform computation using the paradigm of ``metabolic computing''. In this paper we investigate the memory capacity of such computational structures and analyse the trade-off between shape and computation. We now plan to build on these foundations to create a biologically-inspired model in which the encoding of the phenotype is efficient (in terms of the compactness of the genome) and evolvable in tasks involving non-trivial computation, robust to damage and capable of self-maintenance and self-repair.
url http://arxiv.org/pdf/1309.7688v1
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