{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T21:47:14Z","timestamp":1769723234975,"version":"3.49.0"},"reference-count":34,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T00:00:00Z","timestamp":1618963200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Science and Higher education of Russian Federation","award":["FEFE-2020-0013"],"award-info":[{"award-number":["FEFE-2020-0013"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>In this paper, a novel search operation is proposed for the neuroevolution of augmented topologies, namely the difference-based mutation. This operator uses the differences between individuals in the population to perform more efficient search for optimal weights and structure of the model. The difference is determined according to the innovation numbers assigned to each node and connection, allowing tracking the changes. The implemented neuroevolution algorithm allows backward connections and loops in the topology, and uses a set of mutation operators, including connections merging and deletion. The algorithm is tested on a set of classification problems and the rotary inverted pendulum control problem. The comparison is performed between the basic approach and modified versions. The sensitivity to parameter values is examined. The experimental results prove that the newly developed operator delivers significant improvements to the classification quality in several cases, and allow finding better control algorithms.<\/jats:p>","DOI":"10.3390\/a14050127","type":"journal-article","created":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T12:47:07Z","timestamp":1619009227000},"page":"127","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Difference-Based Mutation Operation for Neuroevolution of Augmented Topologies"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1695-5798","authenticated-orcid":false,"given":"Vladimir","family":"Stanovov","sequence":"first","affiliation":[{"name":"Institute of Informatics and Telecommunication, Reshetnev Siberian State University of Science and Technology, 660037 Krasnoyarsk, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2927-1974","authenticated-orcid":false,"given":"Shakhnaz","family":"Akhmedova","sequence":"additional","affiliation":[{"name":"Institute of Informatics and Telecommunication, Reshetnev Siberian State University of Science and Technology, 660037 Krasnoyarsk, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3776-5707","authenticated-orcid":false,"given":"Eugene","family":"Semenkin","sequence":"additional","affiliation":[{"name":"Institute of Informatics and Telecommunication, Reshetnev Siberian State University of Science and Technology, 660037 Krasnoyarsk, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep Learning","volume":"521","author":"Bengio","year":"2015","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long Short-Term Memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1126\/science.1091277","article-title":"Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication","volume":"304","author":"Jaeger","year":"2015","journal-title":"Science"},{"key":"ref_4","unstructured":"Chenxi, L., Zoph, B., Neumann, M., Shlens, J., Hua, W., Li, L.-J., Fei-Fei, L., Yuille, A., Huang, J., and Murphy, K. 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