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Measuring, enabling and comparing modularity, regularity and hierarchy in evolutionary design

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Gregory S. HornbyAuthors Info & Claims

GECCO '05: Proceedings of the 7th annual conference on Genetic and evolutionary computation

Pages 1729 - 1736

https://doi.org/10.1145/1068009.1068297

Published: 25 June 2005 Publication History

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Abstract

For computer-automated design systems to scale to complex designs they must be able to produce designs that exhibit the characteristics of modularity, regularity and hierarchy -- characteristics that are found both in man-made and natural designs. Here we claim that these characteristics are enabled by implementing the attributes of combination, control-flow and abstraction in the representation.To support this claim we use an evolutionary algorithm to evolve solutions to different sizes of a table design problem using five different representations, each with different combinations of modularity, regularity and hierarchy enabled and show that the best performance happens when all three of these attributes are enabled.We also define metrics for modularity, regularity and hierarchy in design encodings and demonstrate that high fitness values are achieved with high values of modularity, regularity and hierarchy and that there is a positive correlation between increases in fitness and increases in the measured values of modularity, regularity and hierarchy.

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Cited By

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Qayumi KNorta A(2018)A Comprehensive Approach for Designing Business-Intelligence Solutions with Multi-agent Systems in Distributed EnvironmentsTransactions on Large-Scale Data- and Knowledge-Centered Systems XXXVII10.1007/978-3-662-57932-9_4(113-150)Online publication date: 2-Aug-2018
https://doi.org/10.1007/978-3-662-57932-9_4
Mengistu HHuizinga JMouret JClune J(2016)The Evolutionary Origins of HierarchyPLOS Computational Biology10.1371/journal.pcbi.100482912:6(e1004829)Online publication date: 9-Jun-2016
https://doi.org/10.1371/journal.pcbi.1004829
Tarapore DMouret J(2015)Evolvability signatures of generative encodingsInformation Sciences: an International Journal10.1016/j.ins.2015.03.046313:C(43-61)Online publication date: 20-Aug-2015
https://dl.acm.org/doi/10.1016/j.ins.2015.03.046
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Index Terms

Measuring, enabling and comparing modularity, regularity and hierarchy in evolutionary design
1. Computing methodologies
  1. Artificial intelligence
    1. Philosophical/theoretical foundations of artificial intelligence

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Published In

GECCO '05: Proceedings of the 7th annual conference on Genetic and evolutionary computation

June 2005

2272 pages

ISBN:1595930108

DOI:10.1145/1068009

Editor:
Hans-Georg Beyer
Vorarlberg University of Applied Sciences, Austria
,
General Chair:
Una-May O'Reilly
CSAIL, MIT

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 25 June 2005

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June 25 - 29, 2005

Washington DC, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Qayumi KNorta A(2018)A Comprehensive Approach for Designing Business-Intelligence Solutions with Multi-agent Systems in Distributed EnvironmentsTransactions on Large-Scale Data- and Knowledge-Centered Systems XXXVII10.1007/978-3-662-57932-9_4(113-150)Online publication date: 2-Aug-2018
https://doi.org/10.1007/978-3-662-57932-9_4
Mengistu HHuizinga JMouret JClune J(2016)The Evolutionary Origins of HierarchyPLOS Computational Biology10.1371/journal.pcbi.100482912:6(e1004829)Online publication date: 9-Jun-2016
https://doi.org/10.1371/journal.pcbi.1004829
Tarapore DMouret J(2015)Evolvability signatures of generative encodingsInformation Sciences: an International Journal10.1016/j.ins.2015.03.046313:C(43-61)Online publication date: 20-Aug-2015
https://dl.acm.org/doi/10.1016/j.ins.2015.03.046
Byrne JFenton MHemberg EMcDermott JO'Neill M(2015)Optimising complex pylon structures with grammatical evolutionInformation Sciences: an International Journal10.1016/j.ins.2014.03.010316:C(582-597)Online publication date: 20-Sep-2015
https://dl.acm.org/doi/10.1016/j.ins.2014.03.010
Calabretta RNeirotti J(2015)Adaptive Agents in Changing Environments, the Role of ModularityNeural Processing Letters10.1007/s11063-014-9355-842:2(257-274)Online publication date: 1-Oct-2015
https://dl.acm.org/doi/10.1007/s11063-014-9355-8
Tonelli PMouret J(2013)On the Relationships between Generative Encodings, Regularity, and Learning Abilities when Evolving Plastic Artificial Neural NetworksPLoS ONE10.1371/journal.pone.00791388:11(e79138)Online publication date: 13-Nov-2013
https://doi.org/10.1371/journal.pone.0079138
Rieffel JAlba E(2013)Heterochronic scaling of developmental durations in evolved soft robotsProceedings of the 15th annual conference on Genetic and evolutionary computation10.1145/2463372.2463466(743-750)Online publication date: 6-Jul-2013
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Harrington ARoss B(2013)Generative representations for artificial architecture and passive solar performance2013 IEEE Congress on Evolutionary Computation10.1109/CEC.2013.6557615(537-545)Online publication date: Jun-2013
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Byrne JHemberg EO'Neill MBrabazon A(2013)A methodology for user directed search in evolutionary designGenetic Programming and Evolvable Machines10.1007/s10710-013-9189-614:3(287-314)Online publication date: 1-Sep-2013
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Cazenille LBredeche NHamann HStradner JMoore J(2012)Impact of neuron models and network structure on evolving modular robot neural network controllersProceedings of the 14th annual conference on Genetic and evolutionary computation10.1145/2330163.2330177(89-96)Online publication date: 7-Jul-2012
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ALPS: the age-layered population structure for reducing the problem of premature convergence

Case-based evolutionary design

Distance-Targeting Mutation Operator for Evolutionary Design of 3D Structures

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