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GI4GI: Improving Genetic Improvement Fitness Functions

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GECCO Companion '15: Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation

Pages 793 - 794

https://doi.org/10.1145/2739482.2768415

Published: 11 July 2015 Publication History

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Abstract

Genetic improvement (GI) has been successfully used to optimise non-functional properties of software, such as execution time, by automatically manipulating program's source code. Measurement of non-functional properties, however, is a non-trivial task; energy consumption, for instance, is highly dependant on the hardware used. Therefore, we propose the GI4GI framework (and two illustrative applications). GI4GI first applies GI to improve the fitness function for the particular environment within which software is subsequently optimised using traditional GI.

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Cited By

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Fredericks EMoore JDiller A(2024)GenerativeGI: creating generative art with genetic improvementAutomated Software Engineering10.1007/s10515-024-00414-331:1Online publication date: 1-Mar-2024
https://doi.org/10.1007/s10515-024-00414-3
Rainford PPorter B(2021)Open Challenges in Genetic Improvement for Emergent Software Systems2021 IEEE/ACM International Workshop on Genetic Improvement (GI)10.1109/GI52543.2021.00018(43-44)Online publication date: May-2021
https://doi.org/10.1109/GI52543.2021.00018
Langdon W(2020)Genetic Improvement of Genetic Programming2020 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC48606.2020.9185771(1-8)Online publication date: Jul-2020
https://doi.org/10.1109/CEC48606.2020.9185771
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GI4GI: Improving Genetic Improvement Fitness Functions

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GECCO Companion '15: Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation

July 2015

1568 pages

ISBN:9781450334884

DOI:10.1145/2739482

Editor:
Sara Silva
Universidade de Lisboa, Portugal
,
General Chair:
Anna I. Esparcia-Alcázar
Universitat Politècnica de València, Spain

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: 11 July 2015

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SIGEVO

GECCO '15: Genetic and Evolutionary Computation Conference

July 11 - 15, 2015

Madrid, Spain

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

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Fredericks EMoore JDiller A(2024)GenerativeGI: creating generative art with genetic improvementAutomated Software Engineering10.1007/s10515-024-00414-331:1Online publication date: 1-Mar-2024
https://doi.org/10.1007/s10515-024-00414-3
Rainford PPorter B(2021)Open Challenges in Genetic Improvement for Emergent Software Systems2021 IEEE/ACM International Workshop on Genetic Improvement (GI)10.1109/GI52543.2021.00018(43-44)Online publication date: May-2021
https://doi.org/10.1109/GI52543.2021.00018
Langdon W(2020)Genetic Improvement of Genetic Programming2020 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC48606.2020.9185771(1-8)Online publication date: Jul-2020
https://doi.org/10.1109/CEC48606.2020.9185771
Petke JHaraldsson SHarman MLangdon WWhite DWoodward J(2018)Genetic Improvement of Software: A Comprehensive SurveyIEEE Transactions on Evolutionary Computation10.1109/TEVC.2017.269321922:3(415-432)Online publication date: Jun-2018
https://doi.org/10.1109/TEVC.2017.2693219
López-López VTrujillo LLegrand P(2018)Applying genetic improvement to a genetic programming library in C++Soft Computing10.1007/s00500-018-03705-6Online publication date: 19-Dec-2018
https://doi.org/10.1007/s00500-018-03705-6

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Reducing Energy Consumption Using Genetic Improvement

Energy Optimisation via Genetic Improvement: A SBSE technique for a new era in Software Development

A survey of genetic improvement search spaces

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