Karine Miras, Arwin Gansekoele, K. Glette, A. Eiben
{"title":"Insights in evolutionary exploration of robot morphology spaces","authors":"Karine Miras, Arwin Gansekoele, K. Glette, A. Eiben","doi":"10.1109/SSCI.2018.8628662","DOIUrl":null,"url":null,"abstract":"In a recent study we have encountered an unexpected result regarding the evolutionary exploration of robot morphology spaces. Specifically, we found that an algorithm driven by selection based on morphological novelty exploredfewerspots in the space of morphologies than another algorithm based on a combination of morphological novelty and some behavioral criterion (speed of movement). Here we revisit these results, perform new analyses, and obtain new insights. These insights clarify the exploration behavior of these algorithms and provide guidelines for designing selection mechanisms for evolutionary robotics.","PeriodicalId":235735,"journal":{"name":"2018 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"33 14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Symposium Series on Computational Intelligence (SSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSCI.2018.8628662","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In a recent study we have encountered an unexpected result regarding the evolutionary exploration of robot morphology spaces. Specifically, we found that an algorithm driven by selection based on morphological novelty exploredfewerspots in the space of morphologies than another algorithm based on a combination of morphological novelty and some behavioral criterion (speed of movement). Here we revisit these results, perform new analyses, and obtain new insights. These insights clarify the exploration behavior of these algorithms and provide guidelines for designing selection mechanisms for evolutionary robotics.