{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T05:55:59Z","timestamp":1770011759827,"version":"3.49.0"},"reference-count":165,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T00:00:00Z","timestamp":1765411200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T00:00:00Z","timestamp":1765411200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Artif Intell Rev"],"DOI":"10.1007\/s10462-025-11433-1","type":"journal-article","created":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T04:52:14Z","timestamp":1765428734000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Reinforcement learning and the Metaverse: a symbiotic collaboration"],"prefix":"10.1007","volume":"59","author":[{"given":"Nada","family":"Elsokkary","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wasif","family":"Khan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammed","family":"Shurrab","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rabeb","family":"Mizouni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shakti","family":"Singh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jamal","family":"Bentahar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Azzam","family":"Mourad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hadi","family":"Otrok","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,12,11]]},"reference":[{"key":"11433_CR1","doi-asserted-by":"crossref","unstructured":"Abilkaiyrkyzy A, Elhagry A, Laamarti F, et\u00a0al (2023) Metaverse key requirements and platforms survey. IEEE Access","DOI":"10.1109\/ACCESS.2023.3325844"},{"issue":"10","key":"11433_CR2","doi-asserted-by":"publisher","first-page":"10733","DOI":"10.1007\/s10462-023-10437-z","volume":"56","author":"R Ahmad","year":"2023","unstructured":"Ahmad R, Alsmadi I, Alhamdani W et al (2023) Zero-day attack detection: a systematic literature review. Artif Intell Rev 56(10):10733\u201310811","journal-title":"Artif Intell Rev"},{"key":"11433_CR3","doi-asserted-by":"publisher","first-page":"11615","DOI":"10.1109\/ACCESS.2023.3344817","volume":"12","author":"I Aliyu","year":"2024","unstructured":"Aliyu I, Oh S, Ko N et al (2024) Dynamic partial computation offloading for the metaverse in in-network computing. IEEE Access 12:11615\u201311630. https:\/\/doi.org\/10.1109\/ACCESS.2023.3344817","journal-title":"IEEE Access"},{"issue":"2","key":"11433_CR4","doi-asserted-by":"publisher","first-page":"1851","DOI":"10.1109\/COMST.2019.2891891","volume":"21","author":"A Alshamrani","year":"2019","unstructured":"Alshamrani A, Myneni S, Chowdhary A et al (2019) A survey on advanced persistent threats: techniques, solutions, challenges, and research opportunities. IEEE Commun Surv Tutor 21(2):1851\u20131877","journal-title":"IEEE Commun Surv Tutor"},{"issue":"6","key":"11433_CR5","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 et al (2017) Deep reinforcement learning: a brief survey. IEEE Signal Process Mag 34(6):26\u201338","journal-title":"IEEE Signal Process Mag"},{"key":"11433_CR6","doi-asserted-by":"crossref","unstructured":"Awadallah A, Eledlebi K, Zemerly J, et\u00a0al (2024) Artificial intelligence-based cybersecurity for the metaverse: research challenges and opportunities. IEEE Commun Surv Tutorials","DOI":"10.1109\/COMST.2024.3442475"},{"key":"11433_CR7","unstructured":"Bai Y, Kadavath S, Kundu S, et\u00a0al (2022) Constitutional AI: harmlessness from ai feedback. arXiv preprint arXiv:2212.08073"},{"key":"11433_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2024.100680","volume":"54","author":"T Baidya","year":"2024","unstructured":"Baidya T, Moh S (2024) Comprehensive survey on resource allocation for edge-computing-enabled metaverse. Comput Sci Rev 54:100680. https:\/\/doi.org\/10.1016\/j.cosrev.2024.100680","journal-title":"Comput Sci Rev"},{"issue":"1","key":"11433_CR9","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1007\/s10994-023-06479-7","volume":"113","author":"Y Bekkemoen","year":"2024","unstructured":"Bekkemoen Y (2024) Explainable reinforcement learning (xrl): a systematic literature review and taxonomy. Mach Learn 113(1):355\u2013441","journal-title":"Mach Learn"},{"key":"11433_CR10","unstructured":"Bommasani R, Hudson DA, Adeli E, et\u00a0al (2021) On the opportunities and risks of foundation models. arXiv preprint arXiv:2108.07258"},{"key":"11433_CR11","doi-asserted-by":"crossref","unstructured":"Cardenas-Robledo LA, Hern\u00e1ndez-Uribe \u00d3, Reta C, et\u00a0al (2022) Extended reality applications in industry 4.0.\u2014a systematic literature review. Telematics Inform 73:101863","DOI":"10.1016\/j.tele.2022.101863"},{"issue":"4","key":"11433_CR12","doi-asserted-by":"publisher","first-page":"5064","DOI":"10.1109\/TVT.2022.3224443","volume":"72","author":"J Chen","year":"2023","unstructured":"Chen J, Yi C, Wang R et al (2023) Learning aided joint sensor activation and mobile charging vehicle scheduling for energy-efficient wrsn-based industrial iot. IEEE Trans Veh Technol 72(4):5064\u20135078. https:\/\/doi.org\/10.1109\/TVT.2022.3224443","journal-title":"IEEE Trans Veh Technol"},{"issue":"1","key":"11433_CR13","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1109\/JIOT.2023.3296075","volume":"11","author":"J Chen","year":"2024","unstructured":"Chen J, Kang J, Xu M et al (2024) Multiagent deep reinforcement learning for dynamic avatar migration in aiot-enabled vehicular metaverses with trajectory prediction. IEEE Internet Things J 11(1):70\u201383. https:\/\/doi.org\/10.1109\/JIOT.2023.3296075","journal-title":"IEEE Internet Things J"},{"issue":"21","key":"11433_CR14","doi-asserted-by":"publisher","first-page":"34749","DOI":"10.1109\/JIOT.2024.3421918","volume":"11","author":"J Chen","year":"2024","unstructured":"Chen J, Shi Y, Yi C et al (2024) Generative-ai-driven human digital twin in iot healthcare: a comprehensive survey. IEEE Internet Things J 11(21):34749\u201334773. https:\/\/doi.org\/10.1109\/JIOT.2024.3421918","journal-title":"IEEE Internet Things J"},{"issue":"6","key":"11433_CR15","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1109\/MNET.2024.3366560","volume":"38","author":"J Chen","year":"2024","unstructured":"Chen J, Yi C, Du H et al (2024) A revolution of personalized healthcare: enabling human digital twin with mobile aigc. IEEE Network 38(6):234\u2013242. https:\/\/doi.org\/10.1109\/MNET.2024.3366560","journal-title":"IEEE Network"},{"issue":"1","key":"11433_CR16","doi-asserted-by":"publisher","first-page":"706","DOI":"10.1109\/COMST.2023.3308717","volume":"26","author":"J Chen","year":"2024","unstructured":"Chen J, Yi C, Okegbile SD et al (2024) Networking architecture and key supporting technologies for human digital twin in personalized healthcare: a comprehensive survey. IEEE Commun Surv Tutorials 26(1):706\u2013746. https:\/\/doi.org\/10.1109\/COMST.2023.3308717","journal-title":"IEEE Commun Surv Tutorials"},{"issue":"3","key":"11433_CR17","doi-asserted-by":"publisher","first-page":"629","DOI":"10.1109\/JSAC.2023.3345399","volume":"42","author":"Q Chen","year":"2024","unstructured":"Chen Q, Li R, Xu X et al (2024) Human-aware dynamic hierarchical network control for distributed metaverse services. IEEE J Sel Areas Commun 42(3):629\u2013642. https:\/\/doi.org\/10.1109\/JSAC.2023.3345399","journal-title":"IEEE J Sel Areas Commun"},{"issue":"5","key":"11433_CR18","doi-asserted-by":"publisher","first-page":"2784","DOI":"10.1109\/TCYB.2023.3310505","volume":"54","author":"W Chen","year":"2024","unstructured":"Chen W, Zeng C, Liang H et al (2024) Multimodality driven impedance-based sim2real transfer learning for robotic multiple peg-in-hole assembly. IEEE Trans Cybern 54(5):2784\u20132797. https:\/\/doi.org\/10.1109\/TCYB.2023.3310505","journal-title":"IEEE Trans Cybern"},{"key":"11433_CR19","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1016\/j.iotcps.2023.12.002","volume":"4","author":"Z Chen","year":"2024","unstructured":"Chen Z, Gan W, Wu J et al (2024) Metaverse for smart cities: a survey. Internet Things Cyber-Phys Syst 4:203\u2013216. https:\/\/doi.org\/10.1016\/j.iotcps.2023.12.002","journal-title":"Internet Things Cyber-Phys Syst"},{"key":"11433_CR20","unstructured":"Chhan D, Novoseller E, Lawhern VJ (2024) Crowd-prefrl: preference-based reward learning from crowds. arXiv preprint arXiv:2401.10941"},{"key":"11433_CR21","unstructured":"Christiano P, Leike J, Brown T, et\u00a0al (2017) Deep reinforcement learning from human preferences. In: Advances in neural information processing systems (NeurIPS)"},{"issue":"5","key":"11433_CR22","doi-asserted-by":"publisher","first-page":"4145","DOI":"10.1109\/TMC.2023.3288085","volume":"23","author":"NH Chu","year":"2024","unstructured":"Chu NH, Hoang DT, Nguyen DN et al (2024) Metaslicing: a novel resource allocation framework for metaverse. IEEE Trans Mob Comput 23(5):4145\u20134162. https:\/\/doi.org\/10.1109\/TMC.2023.3288085","journal-title":"IEEE Trans Mob Comput"},{"key":"11433_CR23","doi-asserted-by":"publisher","unstructured":"Chua TJ, Yu W, Zhao J (2022) Resource allocation for mobile metaverse with the internet of vehicles over 6g wireless communications: A deep reinforcement learning approach. In: 2022 IEEE 8th World forum on internet of things (WF-IoT), pp 1\u20137. https:\/\/doi.org\/10.1109\/WF-IoT54382.2022.10152199","DOI":"10.1109\/WF-IoT54382.2022.10152199"},{"key":"11433_CR24","doi-asserted-by":"crossref","unstructured":"Chua TJ, Yu W, Zhao J (2023) Mobile edge adversarial detection for digital twinning to the metaverse: a deep reinforcement learning approach. IEEE Trans Wirel Commun","DOI":"10.1109\/ICC45041.2023.10279064"},{"issue":"1","key":"11433_CR25","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1109\/TWC.2024.3462760","volume":"24","author":"TJ Chua","year":"2025","unstructured":"Chua TJ, Yu W, Zhao J (2025) Play to earn in augmented reality with mobile edge computing over wireless networks: a deep reinforcement learning approach. IEEE Trans Wirel Commun 24(1):68\u201383. https:\/\/doi.org\/10.1109\/TWC.2024.3462760","journal-title":"IEEE Trans Wirel Commun"},{"key":"11433_CR26","unstructured":"Clemente AV, Castej\u00f3n HN, Chandra A (2017) Efficient parallel methods for deep reinforcement learning. arXiv preprint arXiv:1705.04862"},{"key":"11433_CR27","doi-asserted-by":"crossref","unstructured":"Dai Z (2019) Transformer-xl: attentive language models beyond a fixed-length context. arXiv preprint arXiv:1901.02860","DOI":"10.18653\/v1\/P19-1285"},{"issue":"9","key":"11433_CR28","doi-asserted-by":"publisher","first-page":"8902","DOI":"10.1109\/TMC.2024.3356178","volume":"23","author":"H Du","year":"2024","unstructured":"Du H, Li Z, Niyato D et al (2024) Diffusion-based reinforcement learning for edge-enabled ai-generated content services. IEEE Trans Mob Comput 23(9):8902\u20138918. https:\/\/doi.org\/10.1109\/TMC.2024.3356178","journal-title":"IEEE Trans Mob Comput"},{"key":"11433_CR29","volume":"66","author":"YK Dwivedi","year":"2022","unstructured":"Dwivedi YK, Hughes L, Baabdullah AM et al (2022) Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. Int J Inf Manage 66:102542","journal-title":"Int J Inf Manage"},{"key":"11433_CR30","doi-asserted-by":"crossref","unstructured":"ElDahshan KA, Farouk H, Mofreh E (2022) Deep reinforcement learning based video games: a review. In: 2022 2nd International mobile, intelligent, and ubiquitous computing conference (MIUCC), IEEE, pp 302\u2013309","DOI":"10.1109\/MIUCC55081.2022.9781752"},{"key":"11433_CR31","unstructured":"Espeholt L, Soyer H, Munos R, et\u00a0al (2018) Impala: Scalable distributed deep-rl with importance weighted actor-learner architectures. In: International conference on machine learning, PMLR, pp 1407\u20131416"},{"issue":"10","key":"11433_CR32","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1007\/s10462-024-10881-5","volume":"57","author":"MA Fadhel","year":"2024","unstructured":"Fadhel MA, Duhaim AM, Albahri A et al (2024) Navigating the metaverse: unraveling the impact of artificial intelligence\u2014a comprehensive review and gap analysis. Artif Intell Rev 57(10):264","journal-title":"Artif Intell Rev"},{"key":"11433_CR33","doi-asserted-by":"publisher","first-page":"944","DOI":"10.1109\/OJCOMS.2025.3531318","volume":"6","author":"A Famili","year":"2025","unstructured":"Famili A, Sun S, Atalay T et al (2025) Harnessing meta-reinforcement learning for enhanced tracking in geofencing systems. IEEE Open J Commun Soc 6:944\u2013960. https:\/\/doi.org\/10.1109\/OJCOMS.2025.3531318","journal-title":"IEEE Open J Commun Soc"},{"issue":"4","key":"11433_CR34","doi-asserted-by":"publisher","first-page":"3473","DOI":"10.1109\/TMC.2024.3509680","volume":"24","author":"L Feng","year":"2025","unstructured":"Feng L, Jiang X, Sun Y et al (2025) Resource allocation for metaverse experience optimization: a multi-objective multi-agent evolutionary reinforcement learning approach. IEEE Trans Mob Comput 24(4):3473\u20133488. https:\/\/doi.org\/10.1109\/TMC.2024.3509680","journal-title":"IEEE Trans Mob Comput"},{"key":"11433_CR35","doi-asserted-by":"crossref","unstructured":"Foerster J, Farquhar G, Afouras T, et\u00a0al (2018) Counterfactual multi-agent policy gradients. In: Proceedings of the AAAI conference on artificial intelligence","DOI":"10.1609\/aaai.v32i1.11794"},{"issue":"11","key":"11433_CR36","doi-asserted-by":"publisher","first-page":"6745","DOI":"10.1109\/TCOMM.2023.3300839","volume":"71","author":"X Gao","year":"2023","unstructured":"Gao X, Yi W, Liu Y et al (2023) Multi-objective optimization of urllc-based metaverse services. IEEE Trans Commun 71(11):6745\u20136761. https:\/\/doi.org\/10.1109\/TCOMM.2023.3300839","journal-title":"IEEE Trans Commun"},{"issue":"1","key":"11433_CR37","first-page":"127","volume":"20","author":"J Garc\u00eda","year":"2019","unstructured":"Garc\u00eda J, Fern\u00e1ndez F (2019) A comprehensive survey on safe reinforcement learning. J Mach Learn Res 20(1):127\u2013180","journal-title":"J Mach Learn Res"},{"issue":"4","key":"11433_CR38","doi-asserted-by":"publisher","first-page":"2209","DOI":"10.1109\/TSMC.2022.3231299","volume":"53","author":"J Gu","year":"2023","unstructured":"Gu J, Wang J, Guo X et al (2023) A metaverse-based teaching building evacuation training system with deep reinforcement learning. IEEE Trans Syst Man Cybern Syst 53(4):2209\u20132219. https:\/\/doi.org\/10.1109\/TSMC.2022.3231299","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"11433_CR39","volume-title":"How to time-stamp a digital document","author":"S Haber","year":"1991","unstructured":"Haber S, Stornetta WS (1991) How to time-stamp a digital document. Springer, Berlin"},{"issue":"4","key":"11433_CR40","doi-asserted-by":"publisher","first-page":"2047","DOI":"10.1109\/TSMC.2022.3227919","volume":"53","author":"R Hare","year":"2023","unstructured":"Hare R, Tang Y (2023) Hierarchical deep reinforcement learning with experience sharing for metaverse in education. IEEE Trans Syst Man Cybern Syst 53(4):2047\u20132055. https:\/\/doi.org\/10.1109\/TSMC.2022.3227919","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"11433_CR41","unstructured":"Hayla M, Zhang W, Chen M (2025) Digital twin-assisted reinforcement learning for sim-to-real transfer in cyber\u2013physical systems: a survey. ACM Computing Surveys Early access"},{"issue":"7","key":"11433_CR42","doi-asserted-by":"publisher","first-page":"1749","DOI":"10.1109\/LCOMM.2023.3274649","volume":"27","author":"NT Hoa","year":"2023","unstructured":"Hoa NT, Huy LV, Son BD et al (2023) Dynamic offloading for edge computing-assisted metaverse systems. IEEE Commun Lett 27(7):1749\u20131753. https:\/\/doi.org\/10.1109\/LCOMM.2023.3274649","journal-title":"IEEE Commun Lett"},{"issue":"5","key":"11433_CR43","doi-asserted-by":"publisher","first-page":"2771","DOI":"10.1109\/TCYB.2023.3312647","volume":"54","author":"J Hou","year":"2024","unstructured":"Hou J, Chen G, Li Z et al (2024) Hybrid residual multiexpert reinforcement learning for spatial scheduling of high-density parking lots. IEEE Trans Cybern 54(5):2771\u20132783. https:\/\/doi.org\/10.1109\/TCYB.2023.3312647","journal-title":"IEEE Trans Cybern"},{"issue":"4","key":"11433_CR44","doi-asserted-by":"publisher","first-page":"850","DOI":"10.1109\/JSAC.2023.3345393","volume":"42","author":"X Hou","year":"2024","unstructured":"Hou X, Wang J, Jiang C et al (2024) Efficient federated learning for metaverse via dynamic user selection, gradient quantization and resource allocation. IEEE J Sel Areas Commun 42(4):850\u2013866. https:\/\/doi.org\/10.1109\/JSAC.2023.3345393","journal-title":"IEEE J Sel Areas Commun"},{"key":"11433_CR45","doi-asserted-by":"crossref","unstructured":"Hu S, Shen L, Zhang Y, et\u00a0al (2024a) On transforming reinforcement learning with transformers: the development trajectory. IEEE Trans Pattern Anal Mach Intell","DOI":"10.1109\/TPAMI.2024.3408271"},{"issue":"1","key":"11433_CR46","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1109\/TIV.2023.3312777","volume":"9","author":"X Hu","year":"2024","unstructured":"Hu X, Li S, Huang T et al (2024) How simulation helps autonomous driving: a survey of sim2real, digital twins, and parallel intelligence. IEEE Trans Intell Veh 9(1):593\u2013612. https:\/\/doi.org\/10.1109\/TIV.2023.3312777","journal-title":"IEEE Trans Intell Veh"},{"issue":"13","key":"11433_CR47","doi-asserted-by":"publisher","first-page":"24049","DOI":"10.1109\/JIOT.2024.3391010","volume":"11","author":"Z Huang","year":"2024","unstructured":"Huang Z, Yang P, Zhou C et al (2024) Joint sensing and communication for mmwave vr in metaverse: a meta-learning approach. IEEE Internet Things J 11(13):24049\u201324060. https:\/\/doi.org\/10.1109\/JIOT.2024.3391010","journal-title":"IEEE Internet Things J"},{"issue":"13s","key":"11433_CR48","first-page":"1","volume":"55","author":"J Huh","year":"2023","unstructured":"Huh J, Mohapatra P (2023) A survey of multi-agent reinforcement learning for cooperative tasks. ACM Comput Surv 55(13s):1\u201338","journal-title":"ACM Comput Surv"},{"key":"11433_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.105581","volume":"117","author":"T Huynh-The","year":"2023","unstructured":"Huynh-The T, Pham QV, Pham XQ et al (2023) Artificial intelligence for the metaverse: a survey. Eng Appl Artif Intell 117:105581. https:\/\/doi.org\/10.1016\/j.engappai.2022.105581","journal-title":"Eng Appl Artif Intell"},{"key":"11433_CR50","doi-asserted-by":"publisher","unstructured":"Jin C, Wu F, Wang J et al (2022) Metamgc: a music generation framework for concerts in metaverse. EURASIP J Audio Speech Music Processing 1:31. https:\/\/doi.org\/10.1186\/s13636-022-00261-8","DOI":"10.1186\/s13636-022-00261-8"},{"issue":"12","key":"11433_CR51","doi-asserted-by":"publisher","first-page":"1077","DOI":"10.1038\/s42256-022-00573-6","volume":"4","author":"H Ju","year":"2022","unstructured":"Ju H, Juan R, Gomez R et al (2022) Transferring policy of deep reinforcement learning from simulation to reality for robotics. Nature Mach Intell 4(12):1077\u20131087","journal-title":"Nature Mach Intell"},{"issue":"2","key":"11433_CR52","doi-asserted-by":"publisher","first-page":"430","DOI":"10.1109\/JAS.2023.123993","volume":"11","author":"J Kang","year":"2024","unstructured":"Kang J, Chen J, Xu M et al (2024) Uav-assisted dynamic avatar task migration for vehicular metaverse services: a multi-agent deep reinforcement learning approach. IEEE\/CAA J Autom Sin 11(2):430\u2013445. https:\/\/doi.org\/10.1109\/JAS.2023.123993","journal-title":"IEEE\/CAA J Autom Sin"},{"issue":"22","key":"11433_CR53","doi-asserted-by":"publisher","first-page":"35928","DOI":"10.1109\/JIOT.2024.3391296","volume":"11","author":"J Kang","year":"2024","unstructured":"Kang J, Zhang J, Yang H et al (2024) When metaverses meet vehicle road cooperation: Multiagent drl-based stackelberg game for vehicular twins migration. IEEE Internet Things J 11(22):35928\u201335941. https:\/\/doi.org\/10.1109\/JIOT.2024.3391296","journal-title":"IEEE Internet Things J"},{"issue":"12","key":"11433_CR54","doi-asserted-by":"publisher","first-page":"21021","DOI":"10.1109\/JIOT.2024.3360183","volume":"11","author":"J Kang","year":"2024","unstructured":"Kang J, Zhong Y, Xu M et al (2024) Tiny multiagent drl for twins migration in uav metaverses: a multileader multifollower stackelberg game approach. IEEE Internet Things J 11(12):21021\u201321036. https:\/\/doi.org\/10.1109\/JIOT.2024.3360183","journal-title":"IEEE Internet Things J"},{"key":"11433_CR55","unstructured":"Kaufmann T, Weng P, Bengs V, et\u00a0al (2023) A survey of reinforcement learning from human feedback. arXiv preprint arXiv:2312.14925"},{"key":"11433_CR56","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2024.101121","volume":"25","author":"LU Khan","year":"2024","unstructured":"Khan LU, Guizani M, Niyato D et al (2024) Metaverse for wireless systems: architecture, advances, standardization, and open challenges. Internet Things 25:101121. https:\/\/doi.org\/10.1016\/j.iot.2024.101121","journal-title":"Internet Things"},{"key":"11433_CR57","doi-asserted-by":"publisher","unstructured":"Kim H (2024) Dynamic resource allocation using deep reinforcement learning for 6g metaverse. In: 2024 International conference on artificial intelligence in information and communication (ICAIIC), pp 538\u2013543. https:\/\/doi.org\/10.1109\/ICAIIC60209.2024.10463509","DOI":"10.1109\/ICAIIC60209.2024.10463509"},{"issue":"6","key":"11433_CR58","doi-asserted-by":"publisher","first-page":"4909","DOI":"10.1109\/TITS.2021.3054625","volume":"23","author":"BR Kiran","year":"2021","unstructured":"Kiran BR, Sobh I, Talpaert V et al (2021) Deep reinforcement learning for autonomous driving: a survey. IEEE Trans Intell Transp Syst 23(6):4909\u20134926","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"11","key":"11433_CR59","doi-asserted-by":"publisher","first-page":"1238","DOI":"10.1177\/0278364913495721","volume":"32","author":"J Kober","year":"2013","unstructured":"Kober J, Bagnell JA, Peters J (2013) Reinforcement learning in robotics: a survey. Int J Robot Res 32(11):1238\u20131274","journal-title":"Int J Robot Res"},{"issue":"10","key":"11433_CR60","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1007\/s10462-024-10905-0","volume":"57","author":"G Kou","year":"2024","unstructured":"Kou G, Din\u00e7er H, Pamucar D et al (2024) Artificial intelligence-based expert weighted quantum picture fuzzy rough sets and recommendation system for metaverse investment decision-making priorities. Artif Intell Rev 57(10):279","journal-title":"Artif Intell Rev"},{"key":"11433_CR61","unstructured":"Lee H, Phatale S, Mansoor H, et\u00a0al (2024) Rlaif vs. rlhf: scaling reinforcement learning from human feedback with ai feedback. In: Proceedings of the 41st international conference on machine learning. JMLR.org, ICML\u201924"},{"key":"11433_CR62","doi-asserted-by":"publisher","DOI":"10.3389\/frvir.2021.697667","volume":"2","author":"JJ Lee","year":"2021","unstructured":"Lee JJ, Hu-Au E (2021) E3xr: an analytical framework for ethical, educational and eudaimonic xr design. Front Virtual Reality 2:697667","journal-title":"Front Virtual Reality"},{"key":"11433_CR63","unstructured":"Lee K, Smith LM, Abbeel P, et\u00a0al (2021) Pebble: feedback-efficient interactive reinforcement learning via relabeling experience and unsupervised pre-training. In: Proceedings of the international conference on machine learning (ICML)"},{"issue":"7","key":"11433_CR64","doi-asserted-by":"publisher","first-page":"7195","DOI":"10.1007\/s10462-022-10348-5","volume":"56","author":"Y Lei","year":"2023","unstructured":"Lei Y, Ye D, Shen S et al (2023) New challenges in reinforcement learning: a survey of security and privacy. Artif Intell Rev 56(7):7195\u20137236","journal-title":"Artif Intell Rev"},{"issue":"15","key":"11433_CR65","doi-asserted-by":"publisher","first-page":"13622","DOI":"10.1109\/JIOT.2023.3262687","volume":"10","author":"J Li","year":"2023","unstructured":"Li J, Yi C, Chen J et al (2023) Joint trajectory planning, application placement, and energy renewal for uav-assisted mec: a triple-learner-based approach. IEEE Internet Things J 10(15):13622\u201313636. https:\/\/doi.org\/10.1109\/JIOT.2023.3262687","journal-title":"IEEE Internet Things J"},{"issue":"1","key":"11433_CR66","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1109\/TGCN.2024.3424449","volume":"9","author":"J Li","year":"2025","unstructured":"Li J, Yi C, Chen J et al (2025) A reinforcement learning-based stochastic game for energy-efficient uav swarm-assisted mec with dynamic clustering and scheduling. IEEE Trans Green Commun Netw 9(1):255\u2013270. https:\/\/doi.org\/10.1109\/TGCN.2024.3424449","journal-title":"IEEE Trans Green Commun Netw"},{"key":"11433_CR67","doi-asserted-by":"publisher","unstructured":"Li M, Zhu H, Zhang H, et\u00a0al (2023b) Afl-rl: A reinforcement learning based mutation scheduling optimization method for fuzzing. In: Proceedings of the 2023 7th international conference on high performance compilation, computing and communications. Association for Computing Machinery, New York, NY, USA, HP3C \u201923, pp 46\u201355. https:\/\/doi.org\/10.1145\/3606043.3606050","DOI":"10.1145\/3606043.3606050"},{"issue":"4","key":"11433_CR68","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1109\/MVT.2023.3321172","volume":"18","author":"S Li","year":"2023","unstructured":"Li S, Lin X, Wu J et al (2023) Digital twin and artificial intelligence-empowered panoramic video streaming: reducing transmission latency in the extended reality-assisted vehicular metaverse. IEEE Veh Technol Mag 18(4):56\u201365. https:\/\/doi.org\/10.1109\/MVT.2023.3321172","journal-title":"IEEE Veh Technol Mag"},{"key":"11433_CR69","doi-asserted-by":"publisher","unstructured":"Li X, Deng R, Wei J, et\u00a0al (2025b) Aigc-driven real-time interactive 4d traffic scene generation in vehicular networks. IEEE Network pp 1\u20131. https:\/\/doi.org\/10.1109\/MNET.2025.3545609","DOI":"10.1109\/MNET.2025.3545609"},{"key":"11433_CR70","unstructured":"Li Y (2017) Deep reinforcement learning: an overview. arXiv preprint arXiv:1701.07274"},{"key":"11433_CR71","doi-asserted-by":"publisher","unstructured":"Lin F, Ning W, Zhai H (2022a) Icdvae: An effective self-supervised reinforcement learning method for behavior decisions of non-player characters in metaverse games. In: 2022 IEEE 10th joint international information technology and artificial intelligence conference (ITAIC), pp 1727\u20131731. https:\/\/doi.org\/10.1109\/ITAIC54216.2022.9836631","DOI":"10.1109\/ITAIC54216.2022.9836631"},{"key":"11433_CR72","doi-asserted-by":"publisher","unstructured":"Lin F, Ning W, Zou Z (2022b) Fed-mt-isac: Federated multi-task inverse soft actor-critic for human-like npcs in the metaverse games. In: International conference on intelligent computing, Springer, pp 492\u2013503. https:\/\/doi.org\/10.1007\/978-3-031-13832-4_41","DOI":"10.1007\/978-3-031-13832-4_41"},{"issue":"5","key":"11433_CR73","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1109\/MWC.016.2300111","volume":"30","author":"L Lin","year":"2023","unstructured":"Lin L, Chen Y, Zhou Z et al (2023) When metaverse meets computing power networking: an energy-efficient framework for service placement. IEEE Wirel Commun 30(5):76\u201385. https:\/\/doi.org\/10.1109\/MWC.016.2300111","journal-title":"IEEE Wirel Commun"},{"key":"11433_CR74","doi-asserted-by":"crossref","unstructured":"Liu XY, Rui J, Gao J, et\u00a0al (2021) Finrl-meta: A universe of near-real market environments for data-driven deep reinforcement learning in quantitative finance. arXiv preprint arXiv:2112.06753","DOI":"10.2139\/ssrn.4253139"},{"issue":"22","key":"11433_CR75","doi-asserted-by":"publisher","first-page":"19993","DOI":"10.1109\/JIOT.2023.3283335","volume":"10","author":"Z Long","year":"2023","unstructured":"Long Z, Dong H, Saddik AE (2023) Human-centric resource allocation for the metaverse with multiaccess edge computing. IEEE Internet Things J 10(22):19993\u201320005. https:\/\/doi.org\/10.1109\/JIOT.2023.3283335","journal-title":"IEEE Internet Things J"},{"key":"11433_CR76","doi-asserted-by":"publisher","unstructured":"Long Z, Wang H, Dong H, et\u00a0al (2025) Adaptive social metaverse streaming based on federated multiagent deep reinforcement learning. IEEE Trans Comput Soc Syst, pp 1\u201312. https:\/\/doi.org\/10.1109\/TCSS.2025.3555419","DOI":"10.1109\/TCSS.2025.3555419"},{"issue":"3","key":"11433_CR77","doi-asserted-by":"publisher","first-page":"710","DOI":"10.1109\/JSAC.2023.3345402","volume":"42","author":"I Lotfi","year":"2024","unstructured":"Lotfi I, Niyato D, Sun S et al (2024) Semantic information marketing in the metaverse: a learning-based contract theory framework. IEEE J Sel Areas Commun 42(3):710\u2013723. https:\/\/doi.org\/10.1109\/JSAC.2023.3345402","journal-title":"IEEE J Sel Areas Commun"},{"issue":"9","key":"11433_CR78","doi-asserted-by":"publisher","first-page":"14092","DOI":"10.1109\/TVT.2024.3397707","volume":"73","author":"B Mao","year":"2024","unstructured":"Mao B, Zhou X, Liu J et al (2024) On a cooperative deep reinforcement learning-based multi-objective routing strategy for diversified 6g metaverse services. IEEE Trans Veh Technol 73(9):14092\u201314096. https:\/\/doi.org\/10.1109\/TVT.2024.3397707","journal-title":"IEEE Trans Veh Technol"},{"key":"11433_CR79","doi-asserted-by":"publisher","unstructured":"Mazandarani H, Shokrnezhad M, Taleb T, et\u00a0al (2023) Self-sustaining multiple access with continual deep reinforcement learning for dynamic metaverse applications. In: 2023 IEEE international conference on metaverse computing, networking and applications (MetaCom). IEEE Computer Society, Los Alamitos, CA, pp 65\u201370. https:\/\/doi.org\/10.1109\/MetaCom57706.2023.00024","DOI":"10.1109\/MetaCom57706.2023.00024"},{"key":"11433_CR80","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1109\/TMLCN.2025.3546183","volume":"3","author":"H Mazandarani","year":"2025","unstructured":"Mazandarani H, Shokrnezhad M, Taleb T (2025) A novel multiple access scheme for heterogeneous wireless communications using symmetry-aware continual deep reinforcement learning. IEEE Trans Mach Learn Commun Netw 3:353\u2013368. https:\/\/doi.org\/10.1109\/TMLCN.2025.3546183","journal-title":"IEEE Trans Mach Learn Commun Netw"},{"issue":"4","key":"11433_CR81","first-page":"12","volume":"27","author":"J McCarthy","year":"1955","unstructured":"McCarthy J, Minsky ML, Rochester N et al (1955) A proposal for the dartmouth summer research project on artificial intelligence, august 31. AI Mag 27(4):12\u201312","journal-title":"AI Mag"},{"issue":"1","key":"11433_CR82","doi-asserted-by":"publisher","first-page":"288","DOI":"10.1109\/JSAC.2022.3221993","volume":"41","author":"Z Meng","year":"2023","unstructured":"Meng Z, She C, Zhao G et al (2023) Sampling, communication, and prediction co-design for synchronizing the real-world device and digital model in metaverse. IEEE J Sel Areas Commun 41(1):288\u2013300. https:\/\/doi.org\/10.1109\/JSAC.2022.3221993","journal-title":"IEEE J Sel Areas Commun"},{"issue":"3","key":"11433_CR83","doi-asserted-by":"publisher","first-page":"752","DOI":"10.1109\/JSAC.2023.3345398","volume":"42","author":"Z Meng","year":"2024","unstructured":"Meng Z, Chen K, Diao Y et al (2024) Task-oriented cross-system design for timely and accurate modeling in the metaverse. IEEE J Sel Areas Commun 42(3):752\u2013766. https:\/\/doi.org\/10.1109\/JSAC.2023.3345398","journal-title":"IEEE J Sel Areas Commun"},{"key":"11433_CR84","unstructured":"Metz Y, Lindner D, Baur R, et\u00a0al (2024) Mapping out the space of human feedback for reinforcement learning: a conceptual framework. arXiv preprint arXiv:2411.11761"},{"issue":"7","key":"11433_CR85","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3616864","volume":"56","author":"S Milani","year":"2024","unstructured":"Milani S, Topin N, Veloso M et al (2024) Explainable reinforcement learning: a survey and comparative review. ACM Comput Surv 56(7):1\u201336","journal-title":"ACM Comput Surv"},{"key":"11433_CR86","unstructured":"Nakamoto S (2008) Bitcoin: a peer-to-peer electronic cash system. Satoshi Nakamoto"},{"issue":"2","key":"11433_CR87","doi-asserted-by":"publisher","first-page":"6351","DOI":"10.1016\/j.ifacol.2023.10.818","volume":"56","author":"E Negri","year":"2023","unstructured":"Negri E, Abdel-Aty TA (2023) Clarifying concepts of metaverse, digital twin, digital thread and aas for cps-based production systems. IFAC-PapersOnLine 56(2):6351\u20136357. https:\/\/doi.org\/10.1016\/j.ifacol.2023.10.818","journal-title":"IFAC-PapersOnLine"},{"key":"11433_CR88","unstructured":"Ng AY, Harada D, Russell S (1999) Policy invariance under reward transformations: theory and application to reward shaping. In: Icml, pp 278\u2013287"},{"key":"11433_CR89","unstructured":"Nguyen M, Lin X (2023) Metaverse networking: a survey of communication architectures, technologies, and challenges. IEEE Commun Surv Tutorials Early access"},{"issue":"9","key":"11433_CR90","doi-asserted-by":"publisher","first-page":"3826","DOI":"10.1109\/TCYB.2020.2977374","volume":"50","author":"TT Nguyen","year":"2020","unstructured":"Nguyen TT, Nguyen ND, Nahavandi S (2020) Deep reinforcement learning for multi-agent systems: a review of challenges, solutions, and applications. IEEE Trans Cybern 50(9):3826\u20133839","journal-title":"IEEE Trans Cybern"},{"issue":"11","key":"11433_CR91","doi-asserted-by":"publisher","first-page":"3533","DOI":"10.1109\/JSAC.2023.3310106","volume":"41","author":"SD Okegbile","year":"2023","unstructured":"Okegbile SD, Cai J, Zheng H et al (2023) Differentially private federated multi-task learning framework for enhancing human-to-virtual connectivity in human digital twin. IEEE J Sel Areas Commun 41(11):3533\u20133547. https:\/\/doi.org\/10.1109\/JSAC.2023.3310106","journal-title":"IEEE J Sel Areas Commun"},{"issue":"12","key":"11433_CR92","doi-asserted-by":"publisher","first-page":"22726","DOI":"10.1109\/JIOT.2024.3382829","volume":"11","author":"SD Okegbile","year":"2024","unstructured":"Okegbile SD, Cai J, Chen J et al (2024) A reputation-enhanced shard-based byzantine fault-tolerant scheme for secure data sharing in zero trust human digital twin systems. IEEE Internet Things J 11(12):22726\u201322741. https:\/\/doi.org\/10.1109\/JIOT.2024.3382829","journal-title":"IEEE Internet Things J"},{"issue":"4","key":"11433_CR93","doi-asserted-by":"publisher","first-page":"2440","DOI":"10.1109\/TCCN.2024.3519331","volume":"11","author":"SD Okegbile","year":"2025","unstructured":"Okegbile SD, Cai J, Wu J et al (2025) A prediction-enhanced physical-to-virtual twin connectivity framework for human digital twin. IEEE Trans Cognit Commun Netw 11(4):2440\u20132455. https:\/\/doi.org\/10.1109\/TCCN.2024.3519331","journal-title":"IEEE Trans Cognit Commun Netw"},{"key":"11433_CR94","doi-asserted-by":"publisher","unstructured":"Otoum Y, Gottimukkala N, Kumar N, et\u00a0al (2024) Machine learning in metaverse security: current solutions and future challenges. ACM Comput Surv 56(8). https:\/\/doi.org\/10.1145\/3654663","DOI":"10.1145\/3654663"},{"key":"11433_CR95","first-page":"27730","volume":"35","author":"L Ouyang","year":"2022","unstructured":"Ouyang L, Wu J, Jiang X et al (2022) Training language models to follow instructions with human feedback. Adv Neural Inf Process Syst 35:27730\u201327744","journal-title":"Adv Neural Inf Process Syst"},{"key":"11433_CR96","unstructured":"Pan Z, Liu H (2025) Metaspatial: reinforcing 3d spatial reasoning in vlms for the metaverse. arXiv preprint arXiv:2503.18470"},{"key":"11433_CR97","doi-asserted-by":"publisher","first-page":"54732","DOI":"10.1109\/ACCESS.2024.3390042","volume":"12","author":"S Park","year":"2024","unstructured":"Park S, Baek H, Kim J (2024) Quantum reinforcement learning for spatio-temporal prioritization in metaverse. IEEE Access 12:54732\u201354744. https:\/\/doi.org\/10.1109\/ACCESS.2024.3390042","journal-title":"IEEE Access"},{"issue":"12","key":"11433_CR98","doi-asserted-by":"publisher","first-page":"12410","DOI":"10.1109\/TMC.2024.3407883","volume":"23","author":"S Park","year":"2024","unstructured":"Park S, Chung J, Park C et al (2024) Joint quantum reinforcement learning and stabilized control for spatio-temporal coordination in metaverse. IEEE Trans Mob Comput 23(12):12410\u201312427. https:\/\/doi.org\/10.1109\/TMC.2024.3407883","journal-title":"IEEE Trans Mob Comput"},{"key":"11433_CR99","doi-asserted-by":"publisher","first-page":"4209","DOI":"10.1109\/ACCESS.2021.3140175","volume":"10","author":"SM Park","year":"2022","unstructured":"Park SM, Kim YG (2022) A metaverse: Taxonomy, components, applications, and open challenges. IEEE Access 10:4209\u20134251","journal-title":"IEEE Access"},{"key":"11433_CR100","doi-asserted-by":"publisher","first-page":"125125","DOI":"10.1109\/ACCESS.2024.3452184","volume":"12","author":"A Patra","year":"2024","unstructured":"Patra A, Pandey A, Hassija V et al (2024) A survey on edge enabled metaverse: applications, technological innovations, and prospective trajectories within the industry. IEEE Access 12:125125\u2013125144. https:\/\/doi.org\/10.1109\/ACCESS.2024.3452184","journal-title":"IEEE Access"},{"key":"11433_CR101","doi-asserted-by":"crossref","unstructured":"Peng Z, Liu Z, Zhou B (2025) Data-efficient learning from human interventions for mobile robots. arXiv preprint arXiv:2503.04969","DOI":"10.1109\/ICRA55743.2025.11128012"},{"key":"11433_CR102","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1109\/OJCS.2024.3389462","volume":"5","author":"F Pervez","year":"2024","unstructured":"Pervez F, Shoukat M, Usama M et al (2024) Affective computing and the road to an emotionally intelligent metaverse. IEEE Open J Comput Soc 5:195\u2013214. https:\/\/doi.org\/10.1109\/OJCS.2024.3389462","journal-title":"IEEE Open J Comput Soc"},{"issue":"2","key":"11433_CR103","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1007\/s10846-017-0468-y","volume":"86","author":"AS Polydoros","year":"2017","unstructured":"Polydoros AS, Nalpantidis L (2017) Survey of model-based reinforcement learning: applications on robotics. J Intell Robot Syst 86(2):153\u2013173","journal-title":"J Intell Robot Syst"},{"issue":"8","key":"11433_CR104","doi-asserted-by":"publisher","first-page":"6874","DOI":"10.1109\/TCSVT.2023.3334526","volume":"34","author":"J Pu","year":"2024","unstructured":"Pu J, Duan H, Zhao J et al (2024) Rules for expectation: learning to generate rules via social environment modeling. IEEE Trans Circuits Syst Video Technol 34(8):6874\u20136887. https:\/\/doi.org\/10.1109\/TCSVT.2023.3334526","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"11433_CR105","volume-title":"Markov decision processes: discrete stochastic dynamic programming","author":"ML Puterman","year":"2014","unstructured":"Puterman ML (2014) Markov decision processes: discrete stochastic dynamic programming. Wiley, London"},{"issue":"5","key":"11433_CR106","doi-asserted-by":"publisher","first-page":"2708","DOI":"10.1109\/TCYB.2024.3358739","volume":"54","author":"S Qin","year":"2024","unstructured":"Qin S, Li H, Cheng L (2024) A hybrid controller for musculoskeletal robots targeting lifting tasks in industrial metaverse. IEEE Trans Cybern 54(5):2708\u20132719. https:\/\/doi.org\/10.1109\/TCYB.2024.3358739","journal-title":"IEEE Trans Cybern"},{"issue":"11","key":"11433_CR107","doi-asserted-by":"publisher","first-page":"12128","DOI":"10.1109\/TVT.2022.3190271","volume":"71","author":"Y Ren","year":"2022","unstructured":"Ren Y, Xie R, Yu FR et al (2022) Quantum collective learning and many-to-many matching game in the metaverse for connected and autonomous vehicles. IEEE Trans Veh Technol 71(11):12128\u201312139. https:\/\/doi.org\/10.1109\/TVT.2022.3190271","journal-title":"IEEE Trans Veh Technol"},{"key":"11433_CR108","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1023\/A:1015008417172","volume":"17","author":"C Ribeiro","year":"2002","unstructured":"Ribeiro C (2002) Reinforcement learning agents. Artif Intell Rev 17:223\u2013250. https:\/\/doi.org\/10.1023\/A:1015008417172","journal-title":"Artif Intell Rev"},{"issue":"8","key":"11433_CR109","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10462-025-11243-5","volume":"58","author":"A Sadeghi-Niaraki","year":"2025","unstructured":"Sadeghi-Niaraki A, Rahimi F, Azlan NAEB et al (2025) Groundbreaking taxonomy of metaverse characteristics. Artif Intell Rev 58(8):1\u201350","journal-title":"Artif Intell Rev"},{"key":"11433_CR110","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcan.2024.12.003","author":"S Sai","year":"2024","unstructured":"Sai S, Sharma P, Gaur A et al (2024) Pivotal role of digital twins in the metaverse: a review. Digital Commun Netw. https:\/\/doi.org\/10.1016\/j.dcan.2024.12.003","journal-title":"Digital Commun Netw"},{"key":"11433_CR111","doi-asserted-by":"publisher","first-page":"153171","DOI":"10.1109\/ACCESS.2021.3126658","volume":"9","author":"E Salvato","year":"2021","unstructured":"Salvato E, Fenu G, Medvet E et al (2021) Crossing the reality gap: a survey on sim-to-real transferability of robot controllers in reinforcement learning. IEEE Access 9:153171\u2013153187","journal-title":"IEEE Access"},{"key":"11433_CR112","doi-asserted-by":"crossref","unstructured":"Sami H, Hammoud A, Arafeh M, et\u00a0al (2024) The metaverse: survey, trends, novel pipeline ecosystem and future directions. IEEE Commun Surv Tutorials","DOI":"10.1109\/COMST.2024.3392642"},{"issue":"1","key":"11433_CR113","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1109\/MC.2017.9","volume":"50","author":"M Satyanarayanan","year":"2017","unstructured":"Satyanarayanan M (2017) The emergence of edge computing. Computer 50(1):30\u201339","journal-title":"Computer"},{"key":"11433_CR114","doi-asserted-by":"publisher","unstructured":"Seetohul V, Jahankhani H, Kendzierskyj S, et\u00a0al (2024) Quantum reinforcement learning: advancing ai agents through quantum computing. In: Space law principles and sustainable measures. Springer, pp 55\u201373. https:\/\/doi.org\/10.1007\/978-3-031-64045-2_4","DOI":"10.1007\/978-3-031-64045-2_4"},{"key":"11433_CR115","doi-asserted-by":"publisher","first-page":"5467","DOI":"10.1109\/OJCOMS.2024.3397044","volume":"5","author":"S Sharma","year":"2024","unstructured":"Sharma S, Singh J, Gupta A et al (2024) User safety and security in the metaverse: a critical review. IEEE Open J Commun Soc 5:5467\u20135487. https:\/\/doi.org\/10.1109\/OJCOMS.2024.3397044","journal-title":"IEEE Open J Commun Soc"},{"issue":"4","key":"11433_CR116","doi-asserted-by":"publisher","first-page":"2107","DOI":"10.1109\/TSMC.2022.3229213","volume":"53","author":"H Shi","year":"2023","unstructured":"Shi H, Liu G, Zhang K et al (2023) Marl sim2real transfer: merging physical reality with digital virtuality in metaverse. IEEE Trans Syst Man Cybern Syst 53(4):2107\u20132117. https:\/\/doi.org\/10.1109\/TSMC.2022.3229213","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"issue":"4","key":"11433_CR117","doi-asserted-by":"publisher","first-page":"248","DOI":"10.1109\/MNET.011.2300032","volume":"37","author":"P Si","year":"2023","unstructured":"Si P, Qian L, Zhao J et al (2023) A hybrid framework of reinforcement learning and convex optimization for uav-based autonomous metaverse data collection. IEEE Network 37(4):248\u2013254. https:\/\/doi.org\/10.1109\/MNET.011.2300032","journal-title":"IEEE Network"},{"key":"11433_CR118","doi-asserted-by":"publisher","unstructured":"Si P, Zhao J, Lam KY, et\u00a0al (2023b) Uav-assisted semantic communication with hybrid action reinforcement learning. In: GLOBECOM 2023 - 2023 IEEE global communications conference, pp 3801\u20133806. https:\/\/doi.org\/10.1109\/GLOBECOM54140.2023.10437643","DOI":"10.1109\/GLOBECOM54140.2023.10437643"},{"key":"11433_CR119","first-page":"9460","volume":"35","author":"J Skalse","year":"2022","unstructured":"Skalse J, Howe N, Krasheninnikov D et al (2022) Defining and characterizing reward gaming. Adv Neural Inf Process Syst 35:9460\u20139471","journal-title":"Adv Neural Inf Process Syst"},{"issue":"2","key":"11433_CR120","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1007\/s10462-023-10641-x","volume":"57","author":"MM Soliman","year":"2024","unstructured":"Soliman MM, Ahmed E, Darwish A et al (2024) Artificial intelligence powered metaverse: analysis, challenges and future perspectives. Artif Intell Rev 57(2):36","journal-title":"Artif Intell Rev"},{"key":"11433_CR121","unstructured":"Sukhija B, Zhang H, Singh S, et\u00a0al (2024) Safe multi-agent reinforcement learning: a survey. In: Proceedings of the international joint conference on artificial intelligence (IJCAI)"},{"key":"11433_CR122","unstructured":"Sutherland IE, et\u00a0al (1965) The ultimate display. In: Proceedings of the IFIP Congress, New York, pp 506\u2013508"},{"issue":"3","key":"11433_CR123","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1109\/MWC.020.2200533","volume":"30","author":"B Tan","year":"2023","unstructured":"Tan B, Ai L, Wang M et al (2023) Toward a task offloading framework based on cyber digital twins in mobile edge computing. IEEE Wirel Commun 30(3):157\u2013162. https:\/\/doi.org\/10.1109\/MWC.020.2200533","journal-title":"IEEE Wirel Commun"},{"key":"11433_CR124","unstructured":"Tassa Y, Doron Y, Muldal A, et\u00a0al (2018) Deepmind control suite. arXiv preprint arXiv:1801.00690"},{"key":"11433_CR125","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.111098","volume":"150","author":"M Tavana","year":"2024","unstructured":"Tavana M, Sorooshian S (2024) A systematic review of the soft computing methods shaping the future of the metaverse. Appl Soft Comput 150:111098. https:\/\/doi.org\/10.1016\/j.asoc.2023.111098","journal-title":"Appl Soft Comput"},{"issue":"3","key":"11433_CR126","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1007\/s12193-022-00388-0","volume":"16","author":"S Vlahovic","year":"2022","unstructured":"Vlahovic S, Suznjevic M, Skorin-Kapov L (2022) A survey of challenges and methods for quality of experience assessment of interactive vr applications. J Multimodal User Interfaces 16(3):257\u2013291","journal-title":"J Multimodal User Interfaces"},{"issue":"5","key":"11433_CR127","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3527448","volume":"55","author":"GA Vouros","year":"2022","unstructured":"Vouros GA (2022) Explainable deep reinforcement learning: state of the art and challenges. ACM Comput Surv 55(5):1\u201339","journal-title":"ACM Comput Surv"},{"issue":"16","key":"11433_CR128","doi-asserted-by":"publisher","first-page":"14671","DOI":"10.1109\/JIOT.2023.3278329","volume":"10","author":"H Wang","year":"2023","unstructured":"Wang H, Ning H, Lin Y et al (2023) A survey on the metaverse: the state-of-the-art, technologies, applications, and challenges. IEEE Internet Things J 10(16):14671\u201314688. https:\/\/doi.org\/10.1109\/JIOT.2023.3278329","journal-title":"IEEE Internet Things J"},{"key":"11433_CR129","doi-asserted-by":"crossref","unstructured":"Wang W, Wang R, Mao L, et\u00a0al (2023b) Navistar: socially aware robot navigation with hybrid spatio-temporal graph transformer and preference learning. In: 2023 IEEE\/RSJ international conference on intelligent robots and systems (IROS), IEEE, pp 11348\u201311355","DOI":"10.1109\/IROS55552.2023.10341395"},{"key":"11433_CR130","unstructured":"Wang W, Obi I, Min BC (2024a) Srlm: Human-in-loop interactive social robot navigation with large language model and deep reinforcement learning. arXiv preprint arXiv:2403.15648"},{"key":"11433_CR131","doi-asserted-by":"publisher","unstructured":"Wang X, Cheng N, Ma L, et\u00a0al (2023c) Imperfect digital twin assisted low cost reinforcement training for multi-uav networks. In: 2023 IEEE international conference on metaverse computing, networking and applications (MetaCom), pp 365\u2013369. https:\/\/doi.org\/10.1109\/MetaCom57706.2023.00070","DOI":"10.1109\/MetaCom57706.2023.00070"},{"key":"11433_CR132","doi-asserted-by":"publisher","unstructured":"Wang X, Guo Q, Ning Z, et\u00a0al (2024b) Integration of sensing, communication, and computing for metaverse: a survey. ACM Comput Surv 56(10). https:\/\/doi.org\/10.1145\/3659946","DOI":"10.1145\/3659946"},{"issue":"3","key":"11433_CR133","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1109\/JSAC.2023.3345433","volume":"42","author":"X Wang","year":"2024","unstructured":"Wang X, Li J, Ning Z et al (2024) Wireless powered metaverse: joint task scheduling and trajectory design for multi-devices and multi-uavs. IEEE J Sel Areas Commun 42(3):552\u2013569. https:\/\/doi.org\/10.1109\/JSAC.2023.3345433","journal-title":"IEEE J Sel Areas Commun"},{"issue":"2","key":"11433_CR134","first-page":"885","volume":"10","author":"Y Wang","year":"2023","unstructured":"Wang Y, Guo B, Yu Z et al (2023) Metaverse: survey, applications, security, and opportunities. IEEE Internet Things J 10(2):885\u2013906","journal-title":"IEEE Internet Things J"},{"issue":"5","key":"11433_CR135","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1109\/MWC.009.2300029","volume":"30","author":"Y Wang","year":"2023","unstructured":"Wang Y, He Y, Yu FR et al (2023) Efficient resource allocation for building the metaverse with uavs: a quantum collective reinforcement learning approach. IEEE Wirel Commun 30(5):152\u2013159. https:\/\/doi.org\/10.1109\/MWC.009.2300029","journal-title":"IEEE Wirel Commun"},{"issue":"1","key":"11433_CR136","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1109\/COMST.2022.3202047","volume":"25","author":"Y Wang","year":"2023","unstructured":"Wang Y, Su Z, Zhang N et al (2023) A survey on metaverse: fundamentals, security, and privacy. IEEE Commun Surv Tutorials 25(1):319\u2013352. https:\/\/doi.org\/10.1109\/COMST.2022.3202047","journal-title":"IEEE Commun Surv Tutorials"},{"key":"11433_CR137","unstructured":"Wang Z, Chen K, Jiang J, et\u00a0al (2020) Pop909: a pop-song dataset for music arrangement generation. arXiv preprint arXiv:2008.07142"},{"issue":"6","key":"11433_CR138","doi-asserted-by":"publisher","first-page":"5023","DOI":"10.1007\/s10462-022-10299-x","volume":"56","author":"A Wong","year":"2023","unstructured":"Wong A, B\u00e4ck T, Kononova AV et al (2023) Deep multiagent reinforcement learning: challenges and directions. Artif Intell Rev 56(6):5023\u20135056. https:\/\/doi.org\/10.1007\/s10462-022-10299-x","journal-title":"Artif Intell Rev"},{"key":"11433_CR139","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.eng.2022.05.017","volume":"21","author":"J Wu","year":"2023","unstructured":"Wu J, Huang Z, Hu Z et al (2023) Toward human-in-the-loop ai: enhancing deep reinforcement learning via real-time human guidance for autonomous driving. Engineering 21:75\u201391. https:\/\/doi.org\/10.1016\/j.eng.2022.05.017","journal-title":"Engineering"},{"issue":"12","key":"11433_CR140","doi-asserted-by":"publisher","first-page":"14745","DOI":"10.1109\/TPAMI.2023.3314762","volume":"45","author":"J Wu","year":"2023","unstructured":"Wu J, Zhou Y, Yang H et al (2023) Human-guided reinforcement learning with sim-to-real transfer for autonomous navigation. IEEE Trans Pattern Anal Mach Intell 45(12):14745\u201314759. https:\/\/doi.org\/10.1109\/TPAMI.2023.3314762","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"3","key":"11433_CR141","doi-asserted-by":"publisher","first-page":"2780","DOI":"10.1109\/TNSM.2025.3558358","volume":"22","author":"K Wu","year":"2025","unstructured":"Wu K, Chen J, Chen L et al (2025) Qoe-aware joint visual and haptic signal transmission with adaptive data compression for immersive interactions in human digital twin. IEEE Trans Netw Serv Manage 22(3):2780\u20132794. https:\/\/doi.org\/10.1109\/TNSM.2025.3558358","journal-title":"IEEE Trans Netw Serv Manage"},{"issue":"4","key":"11433_CR142","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1109\/MNET.001.2200563","volume":"37","author":"Z Wu","year":"2023","unstructured":"Wu Z, Xu C, Chen X et al (2023) Bc-metacast: a blockchain-enhanced intelligent computing framework for metaverse livecast. IEEE Netw 37(4):161\u2013168. https:\/\/doi.org\/10.1109\/MNET.001.2200563","journal-title":"IEEE Netw"},{"issue":"2","key":"11433_CR143","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1109\/MMUL.2023.3246528","volume":"30","author":"Y Xiao","year":"2023","unstructured":"Xiao Y, Xu L, Zhang C et al (2023) Blockchain-empowered privacy-preserving digital object trading in the metaverse. IEEE Multimedia 30(2):81\u201390","journal-title":"IEEE Multimedia"},{"key":"11433_CR144","doi-asserted-by":"publisher","first-page":"949","DOI":"10.1016\/j.jmsy.2024.05.001","volume":"74","author":"J Xie","year":"2024","unstructured":"Xie J, Liu Y, Wang X et al (2024) A new xr-based human\u2013robot collaboration assembly system based on industrial metaverse. J Manuf Syst 74:949\u2013964. https:\/\/doi.org\/10.1016\/j.jmsy.2024.05.001","journal-title":"J Manuf Syst"},{"key":"11433_CR145","doi-asserted-by":"publisher","unstructured":"Xu M, Niyato D, Kang J, et\u00a0al (2022) Wireless edge-empowered metaverse: A learning-based incentive mechanism for virtual reality. In: ICC 2022 - IEEE international conference on communications, pp 5220\u20135225, https:\/\/doi.org\/10.1109\/ICC45855.2022.9838736","DOI":"10.1109\/ICC45855.2022.9838736"},{"issue":"1","key":"11433_CR146","doi-asserted-by":"publisher","first-page":"656","DOI":"10.1109\/COMST.2022.3221119","volume":"25","author":"M Xu","year":"2023","unstructured":"Xu M, Ng WC, Lim WYB et al (2023) A full dive into realizing the edge-enabled metaverse: visions, enabling technologies, and challenges. IEEE Commun Surv Tutorials 25(1):656\u2013700. https:\/\/doi.org\/10.1109\/COMST.2022.3221119","journal-title":"IEEE Commun Surv Tutorials"},{"issue":"3","key":"11433_CR147","doi-asserted-by":"publisher","first-page":"783","DOI":"10.1109\/JSAC.2023.3345395","volume":"42","author":"Y Ye","year":"2024","unstructured":"Ye Y, Wang H, Liu CH et al (2024) Qoi-aware mobile crowdsensing for metaverse by multi-agent deep reinforcement learning. IEEE J Sel Areas Commun 42(3):783\u2013798. https:\/\/doi.org\/10.1109\/JSAC.2023.3345395","journal-title":"IEEE J Sel Areas Commun"},{"issue":"6","key":"11433_CR148","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1109\/MNET.2023.3317108","volume":"37","author":"A Yu","year":"2023","unstructured":"Yu A, Yang H, Feng C et al (2023) Socially-aware traffic scheduling for edge-assisted metaverse by deep reinforcement learning. IEEE Network 37(6):74\u201381. https:\/\/doi.org\/10.1109\/MNET.2023.3317108","journal-title":"IEEE Network"},{"key":"11433_CR149","first-page":"1","volume":"36","author":"C Yu","year":"2022","unstructured":"Yu C, Zhang M, Ren F et al (2022) Multi-agent deep reinforcement learning with communication: a survey. Auton Agent Multi-Agent Syst 36:1\u201342","journal-title":"Auton Agent Multi-Agent Syst"},{"issue":"9","key":"11433_CR150","doi-asserted-by":"publisher","first-page":"11276","DOI":"10.1109\/TWC.2024.3380820","volume":"23","author":"J Yu","year":"2024","unstructured":"Yu J, Alhilal AY, Zhou T et al (2024) Attention-based qoe-aware digital twin empowered edge computing for immersive virtual reality. IEEE Trans Wireless Commun 23(9):11276\u201311290. https:\/\/doi.org\/10.1109\/TWC.2024.3380820","journal-title":"IEEE Trans Wireless Commun"},{"key":"11433_CR151","doi-asserted-by":"publisher","unstructured":"Yu W, Zhao J (2023) Heterogeneous 360 degree videos in metaverse: differentiated reinforcement learning approaches. In: GLOBECOM 2023 - 2023 IEEE Global Communications Conference, pp 3336\u20133341. https:\/\/doi.org\/10.1109\/GLOBECOM54140.2023.10436796","DOI":"10.1109\/GLOBECOM54140.2023.10436796"},{"issue":"7","key":"11433_CR152","doi-asserted-by":"publisher","first-page":"2138","DOI":"10.1109\/JSAC.2023.3280988","volume":"41","author":"W Yu","year":"2023","unstructured":"Yu W, Chua TJ, Zhao J (2023) Asynchronous hybrid reinforcement learning for latency and reliability optimization in the metaverse over wireless communications. IEEE J Sel Areas Commun 41(7):2138\u20132157. https:\/\/doi.org\/10.1109\/JSAC.2023.3280988","journal-title":"IEEE J Sel Areas Commun"},{"key":"11433_CR153","doi-asserted-by":"publisher","unstructured":"Yu W, Chua TJ, Zhao J (2023c) Mobile edge computing and ai enabled web3 metaverse over 6g wireless communications: a deep reinforcement learning approach. In: 2023 IEEE 97th Vehicular technology conference (VTC2023-Spring), pp 1\u20135, https:\/\/doi.org\/10.1109\/VTC2023-Spring57618.2023.10199534","DOI":"10.1109\/VTC2023-Spring57618.2023.10199534"},{"key":"11433_CR154","doi-asserted-by":"publisher","unstructured":"Yu W, Chua TJ, Zhao J (2023d) User-centric heterogeneous-action deep reinforcement learning for virtual reality in the metaverse over wireless networks. IEEE Trans Wirel Commun, pp 1\u20131. https:\/\/doi.org\/10.1109\/TWC.2023.3277226","DOI":"10.1109\/TWC.2023.3277226"},{"key":"11433_CR155","doi-asserted-by":"publisher","unstructured":"Yu W, Chua TJ, Zhao J (2023e) Virtual reality in metaverse over wireless networks with user-centered deep reinforcement learning. In: ICC 2023 - IEEE International Conference on Communications, pp 6639\u20136644. https:\/\/doi.org\/10.1109\/ICC45041.2023.10278715","DOI":"10.1109\/ICC45041.2023.10278715"},{"issue":"6","key":"11433_CR156","doi-asserted-by":"publisher","first-page":"763","DOI":"10.1631\/FITEE.2300548","volume":"25","author":"W Yuan","year":"2024","unstructured":"Yuan W, Chen J, Chen S et al (2024) Transformer in reinforcement learning for decision-making: a survey. Front Inf Technol Electron Eng 25(6):763\u2013790","journal-title":"Front Inf Technol Electron Eng"},{"key":"11433_CR157","doi-asserted-by":"publisher","unstructured":"Zhang J, Nie J, Wen J, et\u00a0al (2023a) Learning-based incentive mechanism for task freshness-aware vehicular twin migration. In: 2023 IEEE 43rd international conference on distributed computing systems workshops (ICDCSW), pp 103\u2013108. https:\/\/doi.org\/10.1109\/ICDCSW60045.2023.00020","DOI":"10.1109\/ICDCSW60045.2023.00020"},{"key":"11433_CR158","doi-asserted-by":"crossref","unstructured":"Zhang K, Yang Z, Ba?ar T (2021) Multi-agent reinforcement learning: a selective overview of theories and algorithms. Handbook of Reinforcement Learning and Control, pp 321\u2013384","DOI":"10.1007\/978-3-030-60990-0_12"},{"key":"11433_CR159","doi-asserted-by":"publisher","unstructured":"Zhang W, Chen X, Yin R, et\u00a0al (2024) Information freshness optimization in uav-aided vehicular metaverse: a ppo-based learning approach. In: ICC 2024 - IEEE International Conference on Communications, pp 4755\u20134760. https:\/\/doi.org\/10.1109\/ICC51166.2024.10622700","DOI":"10.1109\/ICC51166.2024.10622700"},{"key":"11433_CR160","doi-asserted-by":"publisher","unstructured":"Zhang X, Min G, Li T, et\u00a0al (2023b) Ai and blockchain empowered metaverse for web 3.0: Vision, architecture, and future directions. IEEE Commun Mag 61(8):60\u201366. https:\/\/doi.org\/10.1109\/MCOM.004.2200473","DOI":"10.1109\/MCOM.004.2200473"},{"key":"11433_CR161","doi-asserted-by":"publisher","unstructured":"Zhang Z, Wang J, Chen J, et\u00a0al (2025) Diffusion-based reinforcement learning for cooperative offloading and resource allocation in multi-uav assisted edge-enabled metaverse. IEEE Trans Veh Technol, pp 1\u201313. https:\/\/doi.org\/10.1109\/TVT.2025.3544879","DOI":"10.1109\/TVT.2025.3544879"},{"key":"11433_CR162","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.comcom.2023.11.024","volume":"214","author":"L Zhao","year":"2024","unstructured":"Zhao L, Yang Q, Huang H et al (2024) Intelligent wireless sensing driven metaverse: a survey. Comput Commun 214:46\u201356. https:\/\/doi.org\/10.1016\/j.comcom.2023.11.024","journal-title":"Comput Commun"},{"key":"11433_CR163","doi-asserted-by":"crossref","unstructured":"Zhao W, Queralta JP, Westerlund T (2020) Sim-to-real transfer in deep reinforcement learning for robotics: a survey. In: 2020 IEEE symposium series on computational intelligence (SSCI). IEEE, pp 737\u2013744","DOI":"10.1109\/SSCI47803.2020.9308468"},{"key":"11433_CR164","doi-asserted-by":"publisher","unstructured":"Zhou X, Mao B, Liu J (2023) A novel multi-objective routing scheme based on cooperative multi-agent reinforcement learning for metaverse services in fixed 6g. In: 2023 32nd Wireless and optical communications conference (WOCC), pp 1\u20135, https:\/\/doi.org\/10.1109\/WOCC58016.2023.10139544","DOI":"10.1109\/WOCC58016.2023.10139544"},{"issue":"3","key":"11433_CR165","doi-asserted-by":"publisher","first-page":"2120","DOI":"10.1109\/COMST.2024.3387124","volume":"26","author":"HY Zhu","year":"2024","unstructured":"Zhu HY, Hieu NQ, Hoang DT et al (2024) A human-centric metaverse enabled by brain-computer interface: a survey. IEEE Commun Surv Tutorials 26(3):2120\u20132145. https:\/\/doi.org\/10.1109\/COMST.2024.3387124","journal-title":"IEEE Commun Surv Tutorials"}],"container-title":["Artificial Intelligence Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-025-11433-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10462-025-11433-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-025-11433-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T03:09:49Z","timestamp":1769483389000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10462-025-11433-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,11]]},"references-count":165,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,1]]}},"alternative-id":["11433"],"URL":"https:\/\/doi.org\/10.1007\/s10462-025-11433-1","relation":{},"ISSN":["1573-7462"],"issn-type":[{"value":"1573-7462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,11]]},"assertion":[{"value":"26 May 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 October 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 December 2025","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 conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"34"}}