Benefits of employing an implicit context representation on hardware geometry of CGP

Authors:
Xinye Cai;Stephen L. Smith;Andy M. Tyrrell
Affiliations:
Department of Electronics, The University of York, Heslington, York, UK;Department of Electronics, The University of York, Heslington, York, UK;Department of Electronics, The University of York, Heslington, York, UK
Venue:
ICES'05 Proceedings of the 6th international conference on Evolvable Systems: from Biology to Hardware
Year:
2005

Citing 7
Cited 1

An adaptive crossover distribution mechanism for genetic algorithms

Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Genetic programming: on the programming of computers by means of natural selection

Genetic programming: on the programming of computers by means of natural selection
Principles in the Evolutionary Design of Digital Circuits—Part I

Genetic Programming and Evolvable Machines
Biomimetic Representation with Genetic Programming Enzyme

Genetic Programming and Evolvable Machines
Image Filter Design with Evolvable Hardware

Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
Cartesian Genetic Programming

Proceedings of the European Conference on Genetic Programming
An implicit context representation for evolving image processing filters

EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing

Multiple Network CGP for the Classification of Mammograms

EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG

Quantified Score

Hi-index	0.00

Visualization

Abstract

Cartesian Genetic Programming (CGP) has successfully been applied to the evolution of simple image processing filters and implemented in intrinsic evolvable hardware by the authors. However, conventional CGP exhibits the undesirable characteristic of positional dependence in which the specific location of genes within the chromosome has a direct or indirect influence on the phenotype. An implicit context representation of CGP (IRCGP) has been implemented by the authors which is positionally independent and outperforms conventional CGP in this application. This paper describes the additional benefits of IRCGP when considering alternative geometries for the hardware components. Results presented show that smaller hardware arrays under IRCGP are more robust and outperform equivalent arrays implemented in conventional CGP.