Browse DORAS
Browse Theses
Search
Latest Additions
Creative Commons License
Except where otherwise noted, content on this site is licensed for use under a:

Evolution of self-maintaining cellular information processing networks

McMullin, Barry and Decraene, James (2011) Evolution of self-maintaining cellular information processing networks. In: Lenaerts, Tom, (ed.) Advances in Artificial Life, ECAL 2011. MIT Press, pp. 530-531. ISBN 978-0-262-29714-1

Full text available as:

[img]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
114Kb

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). 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, crosstalking and multitasking, 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.

Item Type:Book Section
Refereed:Yes
Uncontrolled Keywords:artificial chemistry; evolution
Subjects:Computer Science > Computational complexity
Engineering > Artificial life
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > Research Institute for Networks and Communications Engineering (RINCE)
Publisher:MIT Press
Official URL:http://mitpress.mit.edu/books/chapters/0262297140chap81.pdf
Copyright Information:© 2011 MIT Press
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:EU FP6 Project ESIGNET, contract no. 12789
ID Code:16676
Deposited On:10 Nov 2011 10:48 by Barry McMullin. Last Modified 10 Nov 2011 10:49

Download statistics

Archive Staff Only: edit this record