{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T05:50:20Z","timestamp":1742968220546,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031024610"},{"type":"electronic","value":"9783031024627"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-02462-7_29","type":"book-chapter","created":{"date-parts":[[2022,4,14]],"date-time":"2022-04-14T23:02:49Z","timestamp":1649977369000},"page":"452-467","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Self-adaptation of Neuroevolution Algorithms Using Reinforcement Learning"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0539-2034","authenticated-orcid":false,"given":"Michael","family":"Kogan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2956-5262","authenticated-orcid":false,"given":"Joshua","family":"Karns","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4082-0439","authenticated-orcid":false,"given":"Travis","family":"Desell","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,4,15]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Alba, E., Tomassini, M.: Parallelism and evolutionary algorithms. IEEE Trans. Evol. Comput. 6, 443\u2013462 (2002)","key":"29_CR1","DOI":"10.1109\/TEVC.2002.800880"},{"doi-asserted-by":"crossref","unstructured":"Desell, T.: Large scale evolution of convolutional neural networks using volunteer computing, pp. 127\u2013128 (2017)","key":"29_CR2","DOI":"10.1145\/3067695.3076002"},{"doi-asserted-by":"crossref","unstructured":"Desell, T., ElSaid, A., Ororbia, A.: An Empirical Exploration of Deep Recurrent Connections Using Neuro-Evolution, pp. 546\u2013561 (2020)","key":"29_CR3","DOI":"10.1007\/978-3-030-43722-0_35"},{"doi-asserted-by":"crossref","unstructured":"Floridi, L., Chiriatti, M.: GPT-3: its nature, scope, limits, and consequences. Minds Mach. 30, 1\u201314 (2020)","key":"29_CR4","DOI":"10.2139\/ssrn.3827044"},{"doi-asserted-by":"crossref","unstructured":"Howell, M., Best, M.: On-line PID tuning for engine idle-speed control using continuous action reinforcement learning automata. Control Eng. Pract. 8, 147\u2013154 (2000)","key":"29_CR5","DOI":"10.1016\/S0967-0661(99)00141-0"},{"doi-asserted-by":"crossref","unstructured":"Jardine, P.T., Kogan, M., Givigi, S.N., Yousefi, S.: Adaptive predictive control of a differential drive robot tuned with reinforcement learning 33(2), 410\u2013423 (2018)","key":"29_CR6","DOI":"10.1002\/acs.2882"},{"unstructured":"Jardine, P.: A Reinforcement Learning Approach to Predictive Control Design: Autonomous Vehicle Applications. Ph.D. thesis, May 2018","key":"29_CR7"},{"doi-asserted-by":"crossref","unstructured":"Jardine, P.T., Givigi, S.N., Yousefi, S.: Experimental results for autonomous model-predictive trajectory planning tuned with machine learning. In: 2017 Annual IEEE International Systems Conference (SysCon), pp. 1\u20137 (2017)","key":"29_CR8","DOI":"10.1109\/SYSCON.2017.7934801"},{"doi-asserted-by":"crossref","unstructured":"Kogan, M., Jardine, P.T., Givigi, S.N.: Architecture for testing learning-based autonomous vehicle control design. In: 2018 Annual IEEE International Systems Conference (SysCon), pp. 1\u20137 (2018)","key":"29_CR9","DOI":"10.1109\/SYSCON.2018.8369551"},{"doi-asserted-by":"crossref","unstructured":"Lyu, Z., Karns, J., ElSaid, A., Desell, T.: Improving neuroevolution using island extinction and repopulation, May 2020","key":"29_CR10","DOI":"10.1007\/978-3-030-72699-7_36"},{"doi-asserted-by":"crossref","unstructured":"Matuszewski, J., Rajkowski, A.: The use of machine learning algorithms for image recognition. In: Radioelectronic Systems Conference 2019, vol. 11442, pp. 412\u2013422 (2020)","key":"29_CR11","DOI":"10.1117\/12.2565546"},{"doi-asserted-by":"crossref","unstructured":"Narendra, K.S., Thathachar, M.A.L.: Learning automata - a survey. IEEE Trans. Syst. Man Cybern. SMC-4(4), 323\u2013334 (1974)","key":"29_CR12","DOI":"10.1109\/TSMC.1974.5408453"},{"doi-asserted-by":"crossref","unstructured":"Ororbia, A., ElSaid, A., Desell, T.: Investigating recurrent neural network memory structures using neuro-evolution. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 446\u2013455 (2019)","key":"29_CR13","DOI":"10.1145\/3321707.3321795"},{"doi-asserted-by":"crossref","unstructured":"Radaideh, M.I., Shirvan, K.: Rule-based reinforcement learning methodology to inform evolutionary algorithms for constrained optimization of engineering applications. Knowl. Based Syst. 217, 106836 (2021)","key":"29_CR14","DOI":"10.1016\/j.knosys.2021.106836"},{"doi-asserted-by":"crossref","unstructured":"Barros dos Santos, S.R., Givigi, S.N., Nascimento, C.L.: Autonomous construction of multiple structures using learning automata: description and experimental validation. IEEE Syst. J. 9(4), 1376\u20131387 (2015)","key":"29_CR15","DOI":"10.1109\/JSYST.2014.2374334"},{"doi-asserted-by":"crossref","unstructured":"Sejnowski, T.J.: The unreasonable effectiveness of deep learning in artificial intelligence. In: Proceedings of the National Academy of Sciences, vol. 117(48), pp. 30033\u201330038 (2020)","key":"29_CR16","DOI":"10.1073\/pnas.1907373117"},{"doi-asserted-by":"crossref","unstructured":"Stanley, K.O., Miikkulainen, R.: Evolving neural networks through augmenting topologies. Evol. Computat. 10(2), 99\u2013127 (2002)","key":"29_CR17","DOI":"10.1162\/106365602320169811"},{"doi-asserted-by":"publisher","unstructured":"Thathachar, M.A.L., Sastry, P.S.: Networks of Learning Automata: Techniques for Online Stochastic Optimization. Springer-Verlag, Berlin, Heidelberg (2003). https:\/\/doi.org\/10.1007\/978-1-4419-9052-5","key":"29_CR18","DOI":"10.1007\/978-1-4419-9052-5"},{"key":"29_CR19","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1007\/11564096_42","volume-title":"Machine Learning: ECML 2005","author":"J Vermorel","year":"2005","unstructured":"Vermorel, J., Mohri, M.: Multi-armed bandit algorithms and empirical evaluation. In: Gama, J., Camacho, R., Brazdil, P.B., Jorge, A.M., Torgo, L. (eds.) ECML 2005. LNCS (LNAI), vol. 3720, pp. 437\u2013448. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/11564096_42"},{"doi-asserted-by":"crossref","unstructured":"Weiss, K., Khoshgoftaar, T., Wang, D.: A survey of transfer learning. J. Big Data 3, May 2016","key":"29_CR20","DOI":"10.1186\/s40537-016-0043-6"}],"container-title":["Lecture Notes in Computer Science","Applications of Evolutionary Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-02462-7_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T13:09:33Z","timestamp":1710248973000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-02462-7_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031024610","9783031024627"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-02462-7_29","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"15 April 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EvoApplications","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on the Applications of Evolutionary Computation (Part of EvoStar)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Madrid","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 April 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 April 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"evoapplications2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.evostar.org\/2022\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"67","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"46","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"69% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.1","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1.56","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}