The epigenetic algorithm

Sathish Periyasamy, Alex Gray, Peter Kille

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

12 Citations (Scopus)

Abstract

Evolutionary Computation (EC) paradigms are inspired by the optimization strategies utilized by biological systems. While these strategies can be found in every level of biological organization, almost all of the EC techniques which comprise techniques from Evolutionary Algorithm (EA) to Swarm Intelligence (SI) have been inspired by organism level optimization strategies. While EA is based on transgenerational genetic adaptation of organisms (biologically inspired), SI is mainly based on intra-generational collective behavioral adaptation of organisms (socially inspired). This paper describes the optimization strategies that bio-molecules utilize both for intra-generational and trans-generational adaptation of biological cells. These adaptive strategies which are known as epigenetic mechanisms emerged long before any other biological strategy and form the basis for Epigenetic Algorithms (EGA). Further, the paper proposes an intragenerational EGA based on bio-molecular degradation and autocatalysis which are ubiquitous cellular processes and are pivotal for the adaptive dynamics and evolution of intelligent cellular organization.

Original languageEnglish
Title of host publication2008 IEEE Congress on Evolutionary Computation, CEC 2008
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages3228-3236
Number of pages9
ISBN (Print)9781424418237
DOIs
Publication statusPublished - 2008
Externally publishedYes
EventIEEE Congress on Evolutionary Computation 2008 - Hong Kong, China
Duration: 1 Jun 20086 Jun 2008
https://ieeexplore.ieee.org/xpl/conhome/4625778/proceeding (Proceedings)

Conference

ConferenceIEEE Congress on Evolutionary Computation 2008
Abbreviated titleIEEE CEC 2008
Country/TerritoryChina
CityHong Kong
Period1/06/086/06/08
Internet address

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