The evolution of complexity in self-maintaining cellular information processing networks

DSpace/Manakin Repository


Search DR-NTU

Advanced Search Subject Search


My Account

The evolution of complexity in self-maintaining cellular information processing networks

Show simple item record

dc.contributor.author Decraene, James
dc.contributor.author McMullin, Barry
dc.date.accessioned 2011-07-08T08:03:28Z
dc.date.available 2011-07-08T08:03:28Z
dc.date.copyright 2011
dc.date.issued 2011-07-08
dc.identifier.citation Decraene, J., & Mcmullin, B. (2011). The Evolution of Complexity in Self-maintaining Cellular Information Processing Networks. Advances in Complex Systems, 14(1), 55-75.
dc.identifier.uri http://hdl.handle.net/10220/6873
dc.description.abstract We examine the role of self-maintenance (collective autocatalysis) in the evolution of computational biochemical networks. In primitive proto-cells (lacking separate genetic machinery) self-maintenance is a necessary condition for the direct reproduction and inheritance of what we here term Cellular Information Processing Networks (CIPNs). Indeed, partially reproduced or defective CIPNs may generally lead to malfunctioning or premature death of affected cells. We explore the interaction of this self-maintenance property with the evolution and adaptation of CIPNs capable of distinct information processing abilities. We present an evolutionary simulation platform capable of evolving artificial CIPNs from a bottom-up perspective. This system is an agent-based multi-level selectional Artificial Chemistry (AC) which employs a term rewriting system called the Molecular Classifier System (MCS.bl). The latter is derived from the Holland broadcast language formalism. Using this system, we successfully evolve an artificial CIPN to improve performance on a simple pre-specified information processing task whilst subject to the constraint of continuous self-maintenance. We also describe the evolution of self-maintaining, cross-talking and multi-tasking, CIPNs exhibiting a higher level of topological and functional complexity. This proof of concept aims at contributing to the understanding of the open-ended evolutionary growth of complexity in artificial systems.
dc.relation.ispartofseries Advances in complex systems
dc.rights © 2011 World Scientific Publishing. This is the author created version of a work that has been peer reviewed and accepted for publication by Advances in Complex Systems, World Scientific Publishing. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: http://dx.doi.org/10.1142/S0219525911002913.
dc.subject DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences
dc.title The evolution of complexity in self-maintaining cellular information processing networks
dc.type Journal Article
dc.contributor.school School of Computer Engineering
dc.identifier.doi http://dx.doi.org/10.1142/S0219525911002913
dc.description.version Accepted version
dc.identifier.rims 157311

Files in this item

Files Size Format View
decraene-ACS-09.pdf 442.1Kb PDF View/Open

This item appears in the following Collection(s)

Show simple item record


Total views

All Items Views
The evolution of complexity in self-maintaining cellular information processing networks 476

Total downloads

All Bitstreams Views
decraene-ACS-09.pdf 260

Top country downloads

Country Code Views
China 79
United States of America 77
Singapore 57
France 8
Japan 8

Top city downloads

city Views
Beijing 59
Singapore 56
Mountain View 54
Southampton 4
Paris 3

Downloads / month

  2015-01 2015-02 2015-03 total
decraene-ACS-09.pdf 0 0 1 1