{"title":"Benjamin Doerr and Frank Neumann (editors): theory of evolutionary computation","authors":"Jonathan E. Rowe","doi":"10.1007/s10710-024-09490-6","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":50424,"journal":{"name":"Genetic Programming and Evolvable Machines","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genetic Programming and Evolvable Machines","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10710-024-09490-6","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
期刊介绍：
A unique source reporting on methods for artificial evolution of programs and machines...
Reports innovative and significant progress in automatic evolution of software and hardware.
Features both theoretical and application papers.
Covers hardware implementations, artificial life, molecular computing and emergent computation techniques.
Examines such related topics as evolutionary algorithms with variable-size genomes, alternate methods of program induction, approaches to engineering systems development based on embryology, morphogenesis or other techniques inspired by adaptive natural systems.
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