{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T22:57:50Z","timestamp":1773788270708,"version":"3.50.1"},"reference-count":59,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/L015374\/1"],"award-info":[{"award-number":["EP\/L015374\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"name":"European Union's Horizon Europe Framework Programme","award":["101070596"],"award-info":[{"award-number":["101070596"]}]},{"name":"French 2030 program PEPR O2R"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Evol. Computat."],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1109\/tevc.2024.3376733","type":"journal-article","created":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T19:12:04Z","timestamp":1710357124000},"page":"302-316","source":"Crossref","is-referenced-by-count":9,"title":["Bayesian Optimization for Quality Diversity Search With Coupled Descriptor Functions"],"prefix":"10.1109","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9861-7145","authenticated-orcid":false,"given":"Paul","family":"Kent","sequence":"first","affiliation":[{"name":"University of Warwick, Coventry, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4632-0929","authenticated-orcid":false,"given":"Adam","family":"Gaier","sequence":"additional","affiliation":[{"name":"Autodesk Research, AI Lab, Bonn, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2513-027X","authenticated-orcid":false,"given":"Jean-Baptiste","family":"Mouret","sequence":"additional","affiliation":[{"name":"Universit&#x00E9; de Lorraine, CNRS, Inria, Loria, Nancy, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4343-5878","authenticated-orcid":false,"given":"Juergen","family":"Branke","sequence":"additional","affiliation":[{"name":"Warwick Business School, University of Warwick, Coventry, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Illuminating search spaces by mapping elites","author":"Mouret","year":"2015","journal-title":"arXiv:1504.04909"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.abo2626"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/nature14422"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2017.2735550"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/2463372.2463399"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.3389\/frobt.2016.00040"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1162\/evco_a_00231"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2019.2958211"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58112-1_10"},{"key":"ref10","article-title":"BOP-elites, a Bayesian optimisation algorithm for quality-diversity search","author":"Kent","year":"2020","journal-title":"arXiv:2005.04320"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008306431147"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-66515-9_4"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45712-7_45"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/2001576.2001606"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i7.16740"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3449726.3459490"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-33-6710-4_7"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3449639.3459304"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3449639.3459314"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3389\/frobt.2021.639173"},{"key":"ref21","first-page":"10040","article-title":"Differentiable quality diversity","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Fontaine"},{"key":"ref22","first-page":"1075","article-title":"Diversity policy gradient for sample efficient qualitydiversity optimization","volume-title":"Proc. Genet. Evol. Comput. Conf.","author":"Pierrot"},{"key":"ref23","article-title":"Evolving populations of diverse RL agents with MAP-Elites","author":"Pierrot","year":"2023","journal-title":"arXiv:2303.12803"},{"key":"ref24","article-title":"Proximal policy gradient arborescence for quality diversity reinforcement learning","author":"Batra","year":"2024","journal-title":"arXiv:2305.13795"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2017.2704781"},{"key":"ref26","first-page":"1","article-title":"Evolutionary diversity optimization with clustering-based selection for reinforcement learning","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Wang"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2023\/482"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3390232"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3390217"},{"key":"ref30","first-page":"1","article-title":"Sample-efficient quality-diversity by cooperative coevolution","volume-title":"Proc. Int. Conf. Learn. Represent."},{"key":"ref31","first-page":"158","article-title":"Deep surrogate assisted MAP-Elites for automated hearthstone deckbuilding","volume-title":"Proc. Genet. Evol. Comput. Conf.","author":"Zhang"},{"key":"ref32","first-page":"37762","article-title":"Deep surrogate assisted generation of environments","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Bhatt"},{"key":"ref33","article-title":"Surrogate assisted generation of human-robot interaction scenarios","author":"Bhatt","year":"2023","journal-title":"arXiv:2304.13787"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2023\/611"},{"key":"ref35","article-title":"A tutorial on Bayesian optimization","author":"Frazier","year":"2018","journal-title":"arXiv:1807.02811"},{"key":"ref36","volume-title":"Gaussian Processes Machine Learning","author":"Williams","year":"2005"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1115\/1.3653121"},{"issue":"2","key":"ref38","article-title":"The application of Bayesian methods for seeking the extremum","volume":"2","author":"Mockus","year":"1978","journal-title":"Towards Glob. Optim."},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1137\/100801275"},{"key":"ref40","article-title":"Gaussian process optimization in the bandit setting: No regret and experimental design","author":"Srinivas","year":"2010","journal-title":"arXiv:0912.3995"},{"key":"ref41","first-page":"1","article-title":"DSA-ME: Deep surrogate assisted MAP-Elites","volume-title":"Proc. Workshop Agent Learn. Open-Endedness (ICLR)","author":"Zhang"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3071178.3071282"},{"key":"ref43","first-page":"3330","article-title":"Aerodynamic design exploration through surrogate-assisted illumination","volume-title":"Proc. 18th AIAA\/ISSMO Multidiscip. Anal. Optim. Conf.","author":"Gaier"},{"key":"ref44","first-page":"500","article-title":"Prototype discovery using qualitydiversity","volume-title":"Proc. 15th Int. Conf. Parallel Problem Solv. Nat.","author":"Hagg"},{"key":"ref45","first-page":"1","article-title":"Practical Bayesian optimization of machine learning algorithms","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Snoek"},{"issue":"1","key":"ref46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3425501","article-title":"Greed is good: Exploration and exploitation trade-offs in Bayesian optimisation","volume":"1","author":"De Ath","year":"2021","journal-title":"ACM Trans. Evol. Learn. Optim."},{"issue":"5","key":"ref47","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/0041-5553(76)90154-3","article-title":"Uniformly distributed sequences with an additional uniform property","volume":"16","author":"Sobol","year":"1976","journal-title":"USSR Comput. Math. Math. Phys."},{"key":"ref48","first-page":"775","article-title":"On the scrambled sobo\u00b4l sequence","volume-title":"Proc. Int. Conf. Comput. Sci.","author":"Chi"},{"key":"ref49","first-page":"937","article-title":"Bayesian optimization with inequality constraints","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Gardner"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1145\/321062.321069"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1177\/0361198120936252"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2014.2321134"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/5254.708428"},{"key":"ref54","first-page":"1","article-title":"BoToRCH: A framework for efficient Monte-Carlo Bayesian optimization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Balandat"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2990567"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.926132"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1093\/comjnl\/3.3.175"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-322-89952-1_4"},{"issue":"6","key":"ref59","first-page":"1809","article-title":"Entropy search for informationefficient global optimization","volume":"13","author":"Hennig","year":"2012","journal-title":"J. Mach. Learn. Res."}],"container-title":["IEEE Transactions on Evolutionary Computation"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/4235\/10947080\/10472301.pdf?arnumber=10472301","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,2]],"date-time":"2025-04-02T05:25:29Z","timestamp":1743571529000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10472301\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4]]},"references-count":59,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tevc.2024.3376733","relation":{},"ISSN":["1089-778X","1089-778X","1941-0026"],"issn-type":[{"value":"1089-778X","type":"print"},{"value":"1089-778X","type":"print"},{"value":"1941-0026","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4]]}}}