{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T07:42:53Z","timestamp":1777016573103,"version":"3.51.4"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T00:00:00Z","timestamp":1776988800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T00:00:00Z","timestamp":1776988800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Key projects of scientific research plan of Hubei Provincial Department of Education","award":["D202111802"],"award-info":[{"award-number":["D202111802"]}]},{"name":"Key Research and Development Plan Projects of Hubei Provincial Department of Science and Technology","award":["2022BEC008"],"award-info":[{"award-number":["2022BEC008"]}]},{"name":"Open Fund of Key Laboratory of Cyber-Physical Fusion Intelligent Computing","award":["CPFIC202301"],"award-info":[{"award-number":["CPFIC202301"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"DOI":"10.1007\/s11227-026-08496-4","type":"journal-article","created":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T05:10:42Z","timestamp":1777007442000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An improved crested porcupine optimizer with applications to UAV swarm path planning in complex environments"],"prefix":"10.1007","volume":"82","author":[{"given":"Yahong","family":"Zhai","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingtong","family":"Hang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mao","family":"Xi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yifei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Longyan","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yangbing","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,4,24]]},"reference":[{"issue":"4","key":"8496_CR1","doi-asserted-by":"publisher","first-page":"2684","DOI":"10.1109\/COMST.2024.3395358","volume":"26","author":"P Cao","year":"2024","unstructured":"Cao P, Lei L, Cai S, Shen G, Liu X, Wang X, Zhang L, Zhou L, Guizani M (2024) Computational intelligence algorithms for UAV swarm networking and collaboration: a comprehensive survey and future directions. IEEE Commun Surv Tutor 26(4):2684\u20132728","journal-title":"IEEE Commun Surv Tutor"},{"key":"8496_CR2","doi-asserted-by":"crossref","unstructured":"Ma L, Lin B, Zhang W, Tao J, Zhu X, Chen H (2022) A survey of research on the distributed cooperation method of the UAV swarm based on swarm intelligence. In: 2022 IEEE 13th International Conference on Software Engineering and Service Science (ICSESS), pp. 305\u2013309. IEEE","DOI":"10.1109\/ICSESS54813.2022.9930182"},{"issue":"8","key":"8496_CR3","doi-asserted-by":"publisher","first-page":"400","DOI":"10.3390\/systems11080400","volume":"11","author":"K Telli","year":"2023","unstructured":"Telli K, Kraa O, Himeur Y, Ouamane A, Boumehraz M, Atalla S, Mansoor W (2023) A comprehensive review of recent research trends on unmanned aerial vehicles (UAVs). Systems 11(8):400","journal-title":"Systems"},{"issue":"11","key":"8496_CR4","doi-asserted-by":"publisher","first-page":"19023","DOI":"10.1109\/JIOT.2024.3364230","volume":"11","author":"S Javed","year":"2024","unstructured":"Javed S, Hassan A, Ahmad R, Ahmed W, Ahmed R, Saadat A, Guizani M (2024) State-of-the-art and future research challenges in UAV swarms. IEEE Internet Things J 11(11):19023\u201319045","journal-title":"IEEE Internet Things J"},{"issue":"15","key":"8496_CR5","doi-asserted-by":"publisher","first-page":"13067","DOI":"10.1109\/JIOT.2021.3140066","volume":"9","author":"J Cui","year":"2022","unstructured":"Cui J, Wang L, Hu B, Chen S (2022) Incidence control units selection scheme to enhance the stability of multiple UAVs network. IEEE Internet Things J 9(15):13067\u201313076","journal-title":"IEEE Internet Things J"},{"issue":"13","key":"8496_CR6","doi-asserted-by":"publisher","first-page":"3266","DOI":"10.3390\/rs15133266","volume":"15","author":"M Lyu","year":"2023","unstructured":"Lyu M, Zhao Y, Huang C, Huang H (2023) Unmanned aerial vehicles for search and rescue: a survey. Remote Sens 15(13):3266","journal-title":"Remote Sens"},{"key":"8496_CR7","doi-asserted-by":"crossref","unstructured":"Qu C, Boubin J, Gafurov D, Zhou J, Aloysius N, Nguyen H, Calyam P (2022) UAV swarms in smart agriculture: experiences and opportunities. In: 2022 IEEE 18th International Conference on e-Science (e-Science), pp. 148\u2013158. IEEE","DOI":"10.1109\/eScience55777.2022.00029"},{"issue":"5","key":"8496_CR8","doi-asserted-by":"publisher","first-page":"1096","DOI":"10.3390\/rs14051096","volume":"14","author":"X Lyu","year":"2022","unstructured":"Lyu X, Li X, Dang D, Dou H, Wang K, Lou A (2022) Unmanned aerial vehicle (UAV) remote sensing in grassland ecosystem monitoring: a systematic review. Remote Sens 14(5):1096","journal-title":"Remote Sens"},{"key":"8496_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2024.112015","volume":"164","author":"M Bakirci","year":"2024","unstructured":"Bakirci M (2024) Enhancing vehicle detection in intelligent transportation systems via autonomous UAV platform and yolov8 integration. Appl Soft Comput 164:112015","journal-title":"Appl Soft Comput"},{"issue":"7","key":"8496_CR10","doi-asserted-by":"publisher","first-page":"6068","DOI":"10.1002\/cpe.6068","volume":"34","author":"X Li","year":"2022","unstructured":"Li X, Gong L, Liu X, Jiang F, Shi W, Fan L, Gao H, Li R, Xu J (2022) Solving the last mile problem in logistics: a mobile edge computing and blockchain-based unmanned aerial vehicle delivery system. Concurr Comput Pract Exp 34(7):6068","journal-title":"Concurr Comput Pract Exp"},{"key":"8496_CR11","doi-asserted-by":"crossref","unstructured":"Jyoti J, Batth RS (2021) Unmanned aerial vehicles (UAV) path planning approaches. In: 2021 International Conference on Computing Sciences (ICCS), pp. 76\u201382. IEEE","DOI":"10.1109\/ICCS54944.2021.00023"},{"issue":"4","key":"8496_CR12","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1109\/TRO.2010.2048610","volume":"26","author":"E Besada-Portas","year":"2010","unstructured":"Besada-Portas E, Torre L, Cruz JM, Andr\u00e9s-Toro B (2010) Evolutionary trajectory planner for multiple UAVs in realistic scenarios. IEEE Trans Rob 26(4):619\u2013634","journal-title":"IEEE Trans Rob"},{"issue":"5","key":"8496_CR13","doi-asserted-by":"publisher","first-page":"4295","DOI":"10.1007\/s10462-022-10281-7","volume":"56","author":"J Tang","year":"2023","unstructured":"Tang J, Duan H, Lao S (2023) Swarm intelligence algorithms for multiple unmanned aerial vehicles collaboration: a comprehensive review. Artif Intell Rev 56(5):4295\u20134327","journal-title":"Artif Intell Rev"},{"key":"8496_CR14","doi-asserted-by":"publisher","first-page":"59196","DOI":"10.1109\/ACCESS.2021.3070054","volume":"9","author":"G Tang","year":"2021","unstructured":"Tang G, Tang C, Claramunt C, Hu X, Zhou P (2021) Geometric a-star algorithm: an improved a-star algorithm for AGV path planning in a port environment. IEEE Access 9:59196\u201359210","journal-title":"IEEE Access"},{"issue":"1","key":"8496_CR15","doi-asserted-by":"publisher","first-page":"290","DOI":"10.1109\/TR.2013.2285319","volume":"63","author":"WE Wong","year":"2013","unstructured":"Wong WE, Debroy V, Gao R, Li Y (2013) The DStar method for effective software fault localization. IEEE Trans Reliab 63(1):290\u2013308","journal-title":"IEEE Trans Reliab"},{"issue":"8","key":"8496_CR16","doi-asserted-by":"publisher","first-page":"1439","DOI":"10.1016\/j.combustflame.2010.12.010","volume":"158","author":"KE Niemeyer","year":"2011","unstructured":"Niemeyer KE, Sung C-J (2011) On the importance of graph search algorithms for DRGEP-based mechanism reduction methods. Combust Flame 158(8):1439\u20131443","journal-title":"Combust Flame"},{"issue":"7","key":"8496_CR17","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1177\/0278364906067174","volume":"25","author":"D Hsu","year":"2006","unstructured":"Hsu D, Latombe J-C, Kurniawati H (2006) On the probabilistic foundations of probabilistic roadmap planning. Int J Robot Res 25(7):627\u2013643","journal-title":"Int J Robot Res"},{"issue":"2","key":"8496_CR18","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1109\/JAS.2021.1004252","volume":"9","author":"B Li","year":"2021","unstructured":"Li B, Chen B (2021) An adaptive rapidly-exploring random tree. IEEE\/CAA J Autom Sin 9(2):283\u2013294","journal-title":"IEEE\/CAA J Autom Sin"},{"issue":"6","key":"8496_CR19","doi-asserted-by":"publisher","first-page":"221","DOI":"10.3390\/drones8060221","volume":"8","author":"J Lou","year":"2024","unstructured":"Lou J, Ding R, Wu W (2024) HHPSO: a heuristic hybrid particle swarm optimization path planner for quadcopters. Drones 8(6):221","journal-title":"Drones"},{"key":"8496_CR20","doi-asserted-by":"publisher","first-page":"1103","DOI":"10.1007\/s11831-020-09412-6","volume":"28","author":"M Sharma","year":"2021","unstructured":"Sharma M, Kaur P (2021) A comprehensive analysis of nature-inspired meta-heuristic techniques for feature selection problem. Arch Comput Methods Eng 28:1103\u20131127","journal-title":"Arch Comput Methods Eng"},{"key":"8496_CR21","doi-asserted-by":"crossref","unstructured":"Xie J, He J, Gao Z, Wang S, Liu J, Fan H (2024) An enhanced snow ablation optimizer for UAV swarm path planning and engineering design problems. Heliyon 10(18)","DOI":"10.1016\/j.heliyon.2024.e37819"},{"issue":"1","key":"8496_CR22","doi-asserted-by":"publisher","first-page":"8563","DOI":"10.1038\/s41598-025-92406-w","volume":"15","author":"L Xu","year":"2025","unstructured":"Xu L, Xi M, Gao R, Ye Z, He Z (2025) Dynamic path planning of UAV with least inflection point based on adaptive neighborhood a* algorithm and multi-strategy fusion. Sci Rep 15(1):8563","journal-title":"Sci Rep"},{"key":"8496_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2022.108377","volume":"104","author":"S Jiaqi","year":"2022","unstructured":"Jiaqi S, Li T, Hongtao Z, Xiaofeng L, Tianying X (2022) Adaptive multi-UAV path planning method based on improved Gray Wolf Algorithm. Comput Electr Eng 104:108377","journal-title":"Comput Electr Eng"},{"issue":"7","key":"8496_CR24","doi-asserted-by":"publisher","first-page":"828","DOI":"10.1007\/s11227-025-07335-2","volume":"81","author":"T Xu","year":"2025","unstructured":"Xu T, Chen C, Meng F, Ma D (2025) Exponential-trigonometric optimization algorithm with multi-strategy fusion for UAV three-dimensional path planning. J Supercomput 81(7):828","journal-title":"J Supercomput"},{"key":"8496_CR25","doi-asserted-by":"crossref","unstructured":"Liu B, Jin S, Li Y, Wang Z, Zhao D, Ge W (2025) An asynchronous genetic algorithm for multi-agent path planning inspired by biomimicry. J Bionic Eng 1\u201315","DOI":"10.1007\/s42235-024-00637-w"},{"issue":"4","key":"8496_CR26","doi-asserted-by":"publisher","first-page":"1677","DOI":"10.1007\/s42235-024-00528-0","volume":"21","author":"X Zhang","year":"2024","unstructured":"Zhang X, Yue W (2024) Elite dung beetle optimization algorithm for multi-UAV cooperative search in mountainous environments. J Bionic Eng 21(4):1677\u20131694","journal-title":"J Bionic Eng"},{"key":"8496_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.chaos.2025.116049","volume":"192","author":"Y Dong","year":"2025","unstructured":"Dong Y, Zhang S, Zhang H, Zhou X, Jiang J (2025) Chaotic evolution optimization: a novel metaheuristic algorithm inspired by chaotic dynamics. Chaos, Solitons Fractals 192:116049","journal-title":"Chaos, Solitons Fractals"},{"issue":"1","key":"8496_CR28","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1007\/s10462-024-11008-6","volume":"58","author":"K Ouyang","year":"2024","unstructured":"Ouyang K, Fu S, Chen Y, Cai Q, Heidari AA, Chen H (2024) Escape: an optimization method based on crowd evacuation behaviors. Artif Intell Rev 58(1):19","journal-title":"Artif Intell Rev"},{"key":"8496_CR29","doi-asserted-by":"crossref","unstructured":"Braik M, Al-Hiary H (2025) A novel meta-heuristic optimization algorithm inspired by water uptake and transport in plants. Neural Comput Appl 37(19):13643\u201313724 (1\u201382)","DOI":"10.1007\/s00521-025-11228-z"},{"key":"8496_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2024.117718","volume":"436","author":"Y Lang","year":"2025","unstructured":"Lang Y, Gao Y (2025) Dream optimization algorithm (DOA): a novel metaheuristic optimization algorithm inspired by human dreams and its applications to real-world engineering problems. Comput Methods Appl Mech Eng 436:117718","journal-title":"Comput Methods Appl Mech Eng"},{"key":"8496_CR31","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1007\/s10489-013-0458-0","volume":"40","author":"E Cuevas","year":"2014","unstructured":"Cuevas E, Echavarr\u00eda A, Ram\u00edrez-Orteg\u00f3n MA (2014) An optimization algorithm inspired by the states of matter that improves the balance between exploration and exploitation. Appl Intell 40:256\u2013272","journal-title":"Appl Intell"},{"issue":"1","key":"8496_CR32","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1109\/4235.585893","volume":"1","author":"DH Wolpert","year":"1997","unstructured":"Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1(1):67\u201382","journal-title":"IEEE Trans Evol Comput"},{"key":"8496_CR33","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.111257","volume":"284","author":"M Abdel-Basset","year":"2024","unstructured":"Abdel-Basset M, Mohamed R, Abouhawwash M (2024) Crested porcupine optimizer: a new nature-inspired metaheuristic. Knowl-Based Syst 284:111257","journal-title":"Knowl-Based Syst"},{"key":"8496_CR34","doi-asserted-by":"crossref","unstructured":"Zhang Y, Chen Y, Jiang W (2025) UAV dynamic obstacle avoidance path planning based on improved crested porcupine optimization algorithm. In: Fourth International Conference on Algorithms, Microchips, and Network Applications (AMNA 2025), vol. 13576, pp. 17\u201323. SPIE","DOI":"10.1117\/12.3068468"},{"key":"8496_CR35","doi-asserted-by":"crossref","unstructured":"Liu Z, Tao M (2024) ECPO: an enhanced crested porcupine optimizer. In: 2024 4th International Conference on Communication Technology and Information Technology (ICCTIT), pp. 91\u201397. IEEE","DOI":"10.1109\/ICCTIT64404.2024.10928405"},{"issue":"19","key":"8496_CR36","doi-asserted-by":"publisher","first-page":"3080","DOI":"10.3390\/math12193080","volume":"12","author":"H Liu","year":"2024","unstructured":"Liu H, Zhou R, Zhong X, Yao Y, Shan W, Yuan J, Xiao J, Ma Y, Zhang K, Wang Z (2024) Multi-strategy enhanced crested porcupine optimizer: CAPCPO. Mathematics 12(19):3080","journal-title":"Mathematics"},{"issue":"1","key":"8496_CR37","doi-asserted-by":"publisher","first-page":"20445","DOI":"10.1038\/s41598-024-71485-1","volume":"14","author":"S Liu","year":"2024","unstructured":"Liu S, Jin Z, Lin H, Lu H (2024) An improve crested porcupine algorithm for UAV delivery path planning in challenging environments. Sci Rep 14(1):20445","journal-title":"Sci Rep"},{"key":"8496_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2024.111737","volume":"295","author":"X Wang","year":"2024","unstructured":"Wang X, Sn\u00e1\u0161el V, Mirjalili S, Pan J-S, Kong L, Shehadeh HA (2024) Artificial protozoa optimizer (APO): a novel bio-inspired metaheuristic algorithm for engineering optimization. Knowl-Based Syst 295:111737","journal-title":"Knowl-Based Syst"},{"issue":"10","key":"8496_CR39","doi-asserted-by":"publisher","first-page":"5887","DOI":"10.1002\/int.22535","volume":"36","author":"B Abdollahzadeh","year":"2021","unstructured":"Abdollahzadeh B, Soleimanian Gharehchopogh F, Mirjalili S (2021) Artificial gorilla troops optimizer: a new nature-inspired metaheuristic algorithm for global optimization problems. Int J Intell Syst 36(10):5887\u20135958","journal-title":"Int J Intell Syst"},{"key":"8496_CR40","unstructured":"Wu G, Mallipeddi R, Suganthan PN (2017) Problem definitions and evaluation criteria for the CEC 2017 competition on constrained real-parameter optimization. National University of Defense Technology, Changsha, Hunan, PR China and Kyungpook National University, Daegu, South Korea and Nanyang Technological University, Singapore, Technical Repor"},{"key":"8496_CR41","doi-asserted-by":"crossref","unstructured":"Alsamia S, Albedran H, J\u00e1rmai K (2022) Comparative study of different metaheuristics on CEC 2020 benchmarks. In: Vehicle and Automotive Engineering, pp. 709\u2013719. Springer","DOI":"10.1007\/978-3-031-15211-5_59"},{"key":"8496_CR42","first-page":"353","volume-title":"Problem definitions and evaluation criteria for the CEC 2019 special session on multimodal multiobjective optimization","author":"J-J Liang","year":"2019","unstructured":"Liang J-J, Qu B, Gong D, Yue C (2019) Problem definitions and evaluation criteria for the CEC 2019 special session on multimodal multiobjective optimization. Zhengzhou University, Computational Intelligence Laboratory, pp 353\u2013370"},{"key":"8496_CR43","doi-asserted-by":"crossref","unstructured":"Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of ICNN\u201995-international Conference on Neural Networks, vol. 4, pp. 1942\u20131948. IEEE","DOI":"10.1109\/ICNN.1995.488968"},{"issue":"1","key":"8496_CR44","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1145\/234313.234350","volume":"28","author":"S Forrest","year":"1996","unstructured":"Forrest S (1996) Genetic algorithms ACM Comput Surv (CSUR) 28(1):77\u201380","journal-title":"Genetic algorithms ACM Comput Surv (CSUR)"},{"issue":"4","key":"8496_CR45","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1109\/MCI.2006.329691","volume":"1","author":"M Dorigo","year":"2006","unstructured":"Dorigo M, Birattari M, Stutzle T (2006) Ant colony optimization artificial ants as a computational intelligence technique. IEEE Comput Intell Mag 1(4):28","journal-title":"IEEE Comput Intell Mag"},{"issue":"2","key":"8496_CR46","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1109\/TEVC.2008.927706","volume":"13","author":"AK Qin","year":"2008","unstructured":"Qin AK, Huang VL, Suganthan PN (2008) Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Trans Evol Comput 13(2):398\u2013417","journal-title":"IEEE Trans Evol Comput"},{"key":"8496_CR47","unstructured":"Basturk B (2006) An artificial bee colony (ABC) algorithm for numeric function optimization. In: IEEE Swarm Intelligence Symposium, Indianapolis, IN, USA, 2006, vol. 2006, p. 12"},{"key":"8496_CR48","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","volume":"95","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw 95:51\u201367","journal-title":"Adv Eng Softw"},{"key":"8496_CR49","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1007\/s00521-017-3272-5","volume":"30","author":"H Faris","year":"2018","unstructured":"Faris H, Aljarah I, Al-Betar MA, Mirjalili S (2018) Grey wolf optimizer: a review of recent variants and applications. Neural Comput Appl 30:413\u2013435","journal-title":"Neural Comput Appl"},{"issue":"2","key":"8496_CR50","doi-asserted-by":"publisher","first-page":"268","DOI":"10.1080\/03610926.2017.1408829","volume":"48","author":"C L\u00f3pez-V\u00e1zquez","year":"2019","unstructured":"L\u00f3pez-V\u00e1zquez C, Hochsztain E (2019) Extended and updated tables for the Friedman rank test. Commun Stat Theory Methods 48(2):268\u2013281","journal-title":"Commun Stat Theory Methods"},{"issue":"2","key":"8496_CR51","first-page":"337","volume":"13","author":"T Harris","year":"2013","unstructured":"Harris T, Hardin JW (2013) Exact Wilcoxon signed-rank and Wilcoxon Mann-Whitney ranksum tests. Stand Genomic Sci 13(2):337\u2013343","journal-title":"Stand Genomic Sci"},{"key":"8496_CR52","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1016\/j.neucom.2017.05.059","volume":"266","author":"C YongBo","year":"2017","unstructured":"YongBo C, YueSong M, JianQiao Y, XiaoLong S, Nuo X (2017) Three-dimensional unmanned aerial vehicle path planning using modified wolf pack search algorithm. Neurocomputing 266:445\u2013457","journal-title":"Neurocomputing"},{"issue":"6","key":"8496_CR53","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1109\/MSP.2017.2743240","volume":"34","author":"K Arulkumaran","year":"2017","unstructured":"Arulkumaran K, Deisenroth MP, Brundage M, Bharath AA (2017) Deep reinforcement learning: a brief survey. IEEE Signal Process Mag 34(6):26\u201338","journal-title":"IEEE Signal Process Mag"},{"issue":"1","key":"8496_CR54","doi-asserted-by":"publisher","first-page":"34","DOI":"10.70589\/JRTCSE.2024.1.6","volume":"12","author":"P Roy","year":"2024","unstructured":"Roy P (2024) Enhancing real-world robustness in AI: challenges and solutions. J Recent Trends Comput Sci Eng 12(1):34\u201349","journal-title":"J Recent Trends Comput Sci Eng"},{"key":"8496_CR55","doi-asserted-by":"publisher","DOI":"10.1016\/j.infsof.2020.106368","volume":"127","author":"LE Lwakatare","year":"2020","unstructured":"Lwakatare LE, Raj A, Crnkovic I, Bosch J, Olsson HH (2020) Large-scale machine learning systems in real-world industrial settings: a review of challenges and solutions. Inf Softw Technol 127:106368","journal-title":"Inf Softw Technol"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-026-08496-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-026-08496-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-026-08496-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T07:02:53Z","timestamp":1777014173000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-026-08496-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,24]]},"references-count":55,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2026,4]]}},"alternative-id":["8496"],"URL":"https:\/\/doi.org\/10.1007\/s11227-026-08496-4","relation":{},"ISSN":["1573-0484"],"issn-type":[{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,24]]},"assertion":[{"value":"8 July 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 March 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"372"}}