@prefix config: . @prefix meta: . @prefix rdf: . @prefix rdfs: . @prefix xsd: . @prefix owl: . @prefix dc: . @prefix dcmitype: . @prefix dcterms: . @prefix foaf: . @prefix geo: . @prefix om: . @prefix locn: . @prefix schema: . @prefix skos: . @prefix dbpedia: . @prefix p: . @prefix yago: . @prefix units: . @prefix geonames: . @prefix prv: . @prefix prvTypes: . @prefix doap: . @prefix void: . @prefix ir: . @prefix ou: . @prefix teach: . @prefix time: . @prefix datex: . @prefix aiiso: . @prefix vivo: . @prefix bibo: . @prefix fabio: . @prefix vcard: . @prefix swrcfe: . @prefix frapo: . @prefix org: . @prefix ei2a: . @prefix pto: . vcard:url ; dcterms:contributor "Francisco Fernández de Vega; Gustavo Olague; Francisco Chávez; Daniel Lanza; Wolfgang Banzhaf; Erik Goodman"; ou:bibtex "@Inbook{deVega2020,author={de Vega, Francisco Fern{\\'a}ndez and Olague, Gustavo and Ch{\\'a}vez, Francisco and Lanza, Daniel and Banzhaf, Wolfgang and Goodman, Erik},editor={Banzhaf, Wolfgang and Goodman, Erik and Sheneman, Leigh and Trujillo, Leonardo and Worzel, Bill},title={It Is Time for New Perspectives on How to Fight Bloat in GP},bookTitle={Genetic Programming Theory and Practice XVII},year={2020},publisher={Springer International Publishing},address={Cham},pages={25--38},abstract={The present and future of evolutionary algorithms depends on the proper use of modern parallel and distributed computing infrastructures. Although still sequential approaches dominate the landscape, available multi-core, many-core and distributed systems will make users and researchers to more frequently deploy parallel version of the algorithms. In such a scenario, new possibilities arise regarding the time saved when parallel evaluation of individuals are performed. And this time saving is particularly relevant in Genetic Programming. This paper studies how evaluation time influences not only time to solution in parallel/distributed systems, but may also affect size evolution of individuals in the population, and eventually will reduce the bloat phenomenon GP features. This paper considers time and space as two sides of a single coin when devising a more natural method for fighting bloat. This new perspective allows us to understand that new methods for bloat control can be derived, and the first of such a method is described and tested. Experimental data confirms the strength of the approach: using computing time as a measure of individuals' complexity allows to control the growth in size of genetic programming individuals.},isbn={978-3-030-39958-0},doi={10.1007/978-3-030-39958-0_2},url={https://doi.org/10.1007/978-3-030-39958-0_2}}"; ou:urlOrcid ; vivo:identifier "2020-4134"; dcterms:title "It Is Time for New Perspectives on How to Fight Bloat in GP"; ou:tipoPublicacion "Book Chapter"; dcterms:publisher "Genetic and Evolutionary Computation"; a ou:Publicacion; bibo:doi "10.1007/978-3-030-39958-0_2"; bibo:isbn "9783030399580"; fabio:hasPublicationYear "2020". ou:tienePublicacion .