Caleidgh Bayer, Ryan Amaral, Robert J. Smith, Alexandru Ianta, M. Heywood
{"title":"Finding Simple Solutions to Multi-Task Visual Reinforcement Learning Problems with Tangled Program Graphs","authors":"Caleidgh Bayer, Ryan Amaral, Robert J. Smith, Alexandru Ianta, M. Heywood","doi":"10.1007/978-981-16-8113-4_1","DOIUrl":"https://doi.org/10.1007/978-981-16-8113-4_1","url":null,"abstract":"","PeriodicalId":88876,"journal":{"name":"Genetic and Evolutionary Computation Conference : [proceedings]. Genetic and Evolutionary Computation Conference","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80218415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evolution of the Semiconductor Industry, and the Start of X Law","authors":"A. Sloss","doi":"10.1007/978-981-16-8113-4_11","DOIUrl":"https://doi.org/10.1007/978-981-16-8113-4_11","url":null,"abstract":"","PeriodicalId":88876,"journal":{"name":"Genetic and Evolutionary Computation Conference : [proceedings]. Genetic and Evolutionary Computation Conference","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77148098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Back to the Future—Revisiting OrdinalGP and Trustable Models After a Decade","authors":"M. Kotanchek, N. Haut","doi":"10.1007/978-981-16-8113-4_7","DOIUrl":"https://doi.org/10.1007/978-981-16-8113-4_7","url":null,"abstract":"","PeriodicalId":88876,"journal":{"name":"Genetic and Evolutionary Computation Conference : [proceedings]. Genetic and Evolutionary Computation Conference","volume":"16 9-12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78253571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evolving and Analyzing Modularity with GLEAM (Genetic Learning by Extraction and Absorption of Modules)","authors":"A. Saini, L. Spector","doi":"10.1007/978-981-16-8113-4_10","DOIUrl":"https://doi.org/10.1007/978-981-16-8113-4_10","url":null,"abstract":"","PeriodicalId":88876,"journal":{"name":"Genetic and Evolutionary Computation Conference : [proceedings]. Genetic and Evolutionary Computation Conference","volume":"120 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87823874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Philipp Fleck, Stephan M. Winkler, M. Kommenda, M. Affenzeller
{"title":"Grammar-Based Vectorial Genetic Programming for Symbolic Regression","authors":"Philipp Fleck, Stephan M. Winkler, M. Kommenda, M. Affenzeller","doi":"10.1007/978-981-16-8113-4_2","DOIUrl":"https://doi.org/10.1007/978-981-16-8113-4_2","url":null,"abstract":"","PeriodicalId":88876,"journal":{"name":"Genetic and Evolutionary Computation Conference : [proceedings]. Genetic and Evolutionary Computation Conference","volume":"82 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74519926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Feature Discovery with Deep Learning Algebra Networks","authors":"Michael F. Korns","doi":"10.1007/978-981-16-8113-4_6","DOIUrl":"https://doi.org/10.1007/978-981-16-8113-4_6","url":null,"abstract":"","PeriodicalId":88876,"journal":{"name":"Genetic and Evolutionary Computation Conference : [proceedings]. Genetic and Evolutionary Computation Conference","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83275683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alcides Fonseca, Paulo Canelas, G. Espada, Sara Silva
{"title":"Grammatical Evolution Mapping for Semantically-Constrained Genetic Programming","authors":"Alcides Fonseca, Paulo Canelas, G. Espada, Sara Silva","doi":"10.1007/978-981-16-8113-4_3","DOIUrl":"https://doi.org/10.1007/978-981-16-8113-4_3","url":null,"abstract":"","PeriodicalId":88876,"journal":{"name":"Genetic and Evolutionary Computation Conference : [proceedings]. Genetic and Evolutionary Computation Conference","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89241594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tuong Manh Vu, Charlotte Probst, Joshua M Epstein, Alan Brennan, Mark Strong, Robin C Purshouse
{"title":"Toward inverse generative social science using multi-objective genetic programming.","authors":"Tuong Manh Vu, Charlotte Probst, Joshua M Epstein, Alan Brennan, Mark Strong, Robin C Purshouse","doi":"10.1145/3321707.3321840","DOIUrl":"https://doi.org/10.1145/3321707.3321840","url":null,"abstract":"<p><p>Generative mechanism-based models of social systems, such as those represented by agent-based simulations, require that intra-agent equations (or rules) be specified. However there are often many different choices available for specifying these equations, which can still be interpreted as falling within a particular class of mechanisms. Whilst it is important for a generative model to reproduce historically observed dynamics, it is also important for the model to be theoretically enlightening. Genetic programs (our own included) often produce concatenations that are highly predictive but are complex and hard to interpret theoretically. Here, we develop a new method - based on multi-objective genetic programming - for automating the exploration of both objectives simultaneously. We demonstrate the method by evolving the equations for an existing agent-based simulation of alcohol use behaviors based on social norms theory, the initial model structure for which was developed by a team of human modelers. We discover a trade-off between empirical fit and theoretical interpretability that offers insight into the social norms processes that influence the change and stasis in alcohol use behaviors over time.</p>","PeriodicalId":88876,"journal":{"name":"Genetic and Evolutionary Computation Conference : [proceedings]. Genetic and Evolutionary Computation Conference","volume":"2019 ","pages":"1356-1363"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3321707.3321840","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38514728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}