{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T21:19:12Z","timestamp":1783027152486,"version":"3.54.6"},"reference-count":67,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2027,2,1]],"date-time":"2027-02-01T00:00:00Z","timestamp":1801440000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2027,2,1]],"date-time":"2027-02-01T00:00:00Z","timestamp":1801440000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,2,1]],"date-time":"2027-02-01T00:00:00Z","timestamp":1801440000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2027,2,1]],"date-time":"2027-02-01T00:00:00Z","timestamp":1801440000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2027,2,1]],"date-time":"2027-02-01T00:00:00Z","timestamp":1801440000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2027,2,1]],"date-time":"2027-02-01T00:00:00Z","timestamp":1801440000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2027,2,1]],"date-time":"2027-02-01T00:00:00Z","timestamp":1801440000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2232025G-14"],"award-info":[{"award-number":["2232025G-14"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013804","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013804","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52005099"],"award-info":[{"award-number":["52005099"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Robotics and Computer-Integrated Manufacturing"],"published-print":{"date-parts":[[2027,2]]},"DOI":"10.1016\/j.rcim.2026.103364","type":"journal-article","created":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T07:48:50Z","timestamp":1781596130000},"page":"103364","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Feature fusion-enhanced multi-agent reinforcement learning algorithm for human\u2013robot collaborative flexible job shop scheduling"],"prefix":"10.1016","volume":"103","author":[{"given":"Jinsheng","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9004-9339","authenticated-orcid":false,"given":"Peng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenbing","family":"Xiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongsen","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.rcim.2026.103364_bib0001","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.mechatronics.2018.02.009","article-title":"Survey on human\u2013robot collaboration in industrial settings: safety, intuitive interfaces and applications","volume":"55","author":"Villani","year":"2018","journal-title":"Mechatronics"},{"key":"10.1016\/j.rcim.2026.103364_bib0002","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1108\/IR-02-2020-0039","article-title":"Technology jump in the industry: human\u2013robot cooperation in production","volume":"47","author":"Dobra","year":"2020","journal-title":"Ind. Robot."},{"key":"10.1016\/j.rcim.2026.103364_bib0003","doi-asserted-by":"crossref","DOI":"10.3390\/pr9111910","article-title":"From human-human to human-machine cooperation in manufacturing 4.0","volume":"9","author":"Habib","year":"2021","journal-title":"Processes"},{"key":"10.1016\/j.rcim.2026.103364_bib0004","doi-asserted-by":"crossref","DOI":"10.1016\/j.rcim.2024.102937","article-title":"Reviewing human-robot collaboration in manufacturing: opportunities and challenges in the context of industry 5.0","volume":"93","author":"Dhanda","year":"2025","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"10.1016\/j.rcim.2026.103364_bib0005","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1016\/j.jmsy.2025.07.003","article-title":"From human-related to human-centric: a review of shop floor scheduling problem under Industry 5.0","volume":"82","author":"Gao","year":"2025","journal-title":"J. Manuf. Syst."},{"key":"10.1016\/j.rcim.2026.103364_bib0006","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.jmsy.2023.01.004","article-title":"Flexible job shop scheduling problem under Industry 5.0: a survey on human reintegration, environmental consideration and resilience improvement","volume":"67","author":"Destouet","year":"2023","journal-title":"J. Manuf. Syst."},{"key":"10.1016\/j.rcim.2026.103364_bib0007","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1007\/s10479-005-3446-x","article-title":"Mixed integer linear programming in process scheduling: modeling, algorithms, and applications","volume":"139","author":"Floudas","year":"2005","journal-title":"Ann. Oper. Res."},{"key":"10.1016\/j.rcim.2026.103364_bib0008","doi-asserted-by":"crossref","DOI":"10.1016\/j.rcim.2023.102620","article-title":"Fast scheduling of human-robot teams collaboration on synchronised production-logistics tasks in aircraft assembly","volume":"85","author":"Guo","year":"2024","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"10.1016\/j.rcim.2026.103364_bib0009","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2020.106208","article-title":"Dynamic scheduling for flexible job shop with new job insertions by deep reinforcement learning","volume":"91","author":"Luo","year":"2020","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.rcim.2026.103364_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.rcim.2022.102404","article-title":"Human-robot interactions in manufacturing: a survey of human behavior modeling","volume":"78","author":"Jahanmahin","year":"2022","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"10.1016\/j.rcim.2026.103364_bib0011","doi-asserted-by":"crossref","first-page":"24611","DOI":"10.52202\/068431-1787","article-title":"The surprising effectiveness of PPO in cooperative multi-agent games","volume":"35","author":"Yu","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.rcim.2026.103364_bib0012","series-title":"Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems","first-page":"586","article-title":"Implementing an online scheduling approach for production with multi agent proximal policy optimization (MAPPO)","author":"Lohse","year":"2021"},{"key":"10.1016\/j.rcim.2026.103364_bib0013","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1177\/00187208221077722","article-title":"Human robot collaboration for enhancing work activities","volume":"66","author":"Liu","year":"2024","journal-title":"Hum. Factors"},{"key":"10.1016\/j.rcim.2026.103364_bib0014","doi-asserted-by":"crossref","first-page":"688","DOI":"10.1016\/j.procs.2024.01.068","article-title":"Task allocation in human-robot collaboration: a simulation-based approach to optimize operator\u2019s productivity and ergonomics","volume":"232","author":"Baratta","year":"2024","journal-title":"Procedia Comput. Sci."},{"key":"10.1016\/j.rcim.2026.103364_bib0015","article-title":"Human\u2013robot collaboration in construction: robot design, perception and interaction, and task allocation and execution","volume":"65","author":"Liu","year":"2025","journal-title":"Adv. Eng. Inform."},{"key":"10.1016\/j.rcim.2026.103364_bib0016","doi-asserted-by":"crossref","first-page":"1071","DOI":"10.1007\/s00170-024-13385-2","article-title":"Multimodal perception-fusion-control and human\u2013robot collaboration in manufacturing: a review","volume":"132","author":"Duan","year":"2024","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"10.1016\/j.rcim.2026.103364_bib0017","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.122465","article-title":"Optimal layout planning for human robot collaborative assembly systems and visualization through immersive technologies","volume":"241","author":"Eswaran","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.rcim.2026.103364_bib0018","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/s41693-025-00165-x","article-title":"Exploring AR-enabled human\u2013robot collaboration (HRC) system for exploratory collaborative assembly tasks","volume":"9","author":"Loy","year":"2025","journal-title":"Constr. Robot."},{"key":"10.1016\/j.rcim.2026.103364_bib0019","doi-asserted-by":"crossref","first-page":"540","DOI":"10.3390\/machines12080540","article-title":"A survey of augmented reality for human\u2013robot collaboration","volume":"12","author":"Chang","year":"2024","journal-title":"Machines"},{"key":"10.1016\/j.rcim.2026.103364_bib0020","doi-asserted-by":"crossref","first-page":"515","DOI":"10.3390\/su18010515","article-title":"A comprehensive review of human-robot collaborative manufacturing systems: technologies, applications, and future trends","volume":"18","author":"Cai","year":"2026","journal-title":"Sustainability"},{"key":"10.1016\/j.rcim.2026.103364_bib0021","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijpe.2024.109207","article-title":"Balancing and scheduling of assembly line with multi-type collaborative robots","volume":"271","author":"Mao","year":"2024","journal-title":"Int. J. Prod. Econ."},{"key":"10.1016\/j.rcim.2026.103364_bib0022","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijpe.2021.108094","article-title":"Scheduling human-robot teams in collaborative working cells","volume":"235","author":"Ferreira","year":"2021","journal-title":"Int. J. Prod. Econ."},{"key":"10.1016\/j.rcim.2026.103364_bib0023","doi-asserted-by":"crossref","DOI":"10.1016\/j.tre.2025.104299","article-title":"A novel real-world human-robot collaboration scheduling problem: a combination of assembly line balancing and flow shop scheduling","volume":"202","author":"Ding","year":"2025","journal-title":"Transp. Res. Part E Logist. Transp. Rev."},{"key":"10.1016\/j.rcim.2026.103364_bib0024","first-page":"117","article-title":"An innovative meta\u2013heuristic for balancing and scheduling human\u2013robot collaborative assembly lines in Industry 5.0","volume":"43","author":"Zhang","year":"2026","journal-title":"J. Ind. Prod. Eng."},{"key":"10.1016\/j.rcim.2026.103364_bib0025","first-page":"1","article-title":"Multi-objective metaheuristic approach for balancing and scheduling human-robot collaborative assembly lines with cognitive and ergonomic considerations","author":"Zhang","year":"2026","journal-title":"Int. J. Prod. Res."},{"key":"10.1016\/j.rcim.2026.103364_bib0026","doi-asserted-by":"crossref","first-page":"3397","DOI":"10.3390\/electronics14173397","article-title":"An efficient job insertion algorithm for hybrid human\u2013machine collaborative flexible job shop scheduling with random job arrivals","volume":"14","author":"Song","year":"2025","journal-title":"Electronics"},{"key":"10.1016\/j.rcim.2026.103364_bib0027","doi-asserted-by":"crossref","first-page":"963","DOI":"10.1109\/TII.2023.3271749","article-title":"Human\u2013robot collaborative scheduling in energy-efficient welding shop","volume":"20","author":"Lu","year":"2024","journal-title":"IEEE Trans. Ind. Inform."},{"key":"10.1016\/j.rcim.2026.103364_bib0028","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.121946","article-title":"Task-oriented safety field for robot control in human-robot collaborative assembly based on residual learning","volume":"238","author":"Zhu","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.rcim.2026.103364_bib0029","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2025.111133","article-title":"Dynamic task allocations with Q-learning based particle swarm optimization for human-robot collaboration disassembly of electric vehicle battery recycling","volume":"204","author":"Xiao","year":"2025","journal-title":"Comput. Ind. Eng."},{"key":"10.1016\/j.rcim.2026.103364_bib0030","series-title":"Proceedings of the 2021 20th International Conference on Advanced Robotics (ICAR)","first-page":"927","article-title":"Explainable reinforcement learning for Human-robot collaboration","author":"Iucci","year":"2021"},{"key":"10.1016\/j.rcim.2026.103364_bib0031","first-page":"5","article-title":"Reinforcement learning for robot manipulation tasks in human-robot collaboration using the CQL\/SAC algorithms","volume":"20","author":"Husakovic","year":"2025","journal-title":"Adv. Prod. Eng. Manag."},{"key":"10.1016\/j.rcim.2026.103364_bib0032","doi-asserted-by":"crossref","first-page":"13907","DOI":"10.1109\/TASE.2025.3557155","article-title":"Dynamic disassembly planning of end-of-life products for human\u2013robot collaboration enabled by multi-agent deep reinforcement learning","volume":"22","author":"Peng","year":"2025","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"10.1016\/j.rcim.2026.103364_bib0033","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1016\/j.ifacol.2024.09.266","article-title":"Human-robot collaborative reinforcement learning in semi-automated manufacturing operations","volume":"58","author":"Ajidarma","year":"2024","journal-title":"IFAC-PapersOnLine"},{"key":"10.1016\/j.rcim.2026.103364_bib0034","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/j.ifacol.2025.12.023","article-title":"Value-based reinforcement learning for task scheduling in human-robot applications","volume":"59","author":"Binotto","year":"2025","journal-title":"IFAC-PapersOnLine"},{"key":"10.1016\/j.rcim.2026.103364_bib0035","doi-asserted-by":"crossref","first-page":"3696","DOI":"10.3390\/electronics13183696","article-title":"A deep reinforcement learning method based on a transformer model for the flexible job shop scheduling problem","volume":"13","author":"Xu","year":"2024","journal-title":"Electronics"},{"key":"10.1016\/j.rcim.2026.103364_bib0036","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1016\/j.jmsy.2021.07.015","article-title":"Optimizing task scheduling in human-robot collaboration with deep multi-agent reinforcement learning","volume":"60","author":"Yu","year":"2021","journal-title":"J. Manuf. Syst."},{"key":"10.1016\/j.rcim.2026.103364_bib0037","doi-asserted-by":"crossref","first-page":"163868","DOI":"10.1109\/ACCESS.2020.3021904","article-title":"Mastering the working sequence in human-robot collaborative assembly based on reinforcement learning","volume":"8","author":"Yu","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.rcim.2026.103364_bib0038","doi-asserted-by":"crossref","DOI":"10.1016\/j.rcim.2022.102324","article-title":"Solving job scheduling problems in a resource preemption environment with multi-agent reinforcement learning","volume":"77","author":"Wang","year":"2022","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"10.1016\/j.rcim.2026.103364_bib0039","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.132213","article-title":"JSHM: a dynamic flexible job-shop scheduling method with human-machine collaboration","volume":"666","author":"An","year":"2026","journal-title":"Neurocomputing"},{"key":"10.1016\/j.rcim.2026.103364_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.cor.2024.106914","article-title":"Graph neural networks for job shop scheduling problems: a survey","volume":"176","author":"Smit","year":"2025","journal-title":"Comput. Oper. Res."},{"key":"10.1016\/j.rcim.2026.103364_bib0041","doi-asserted-by":"crossref","DOI":"10.1016\/j.cor.2025.107139","article-title":"Flexible job shop scheduling problem using graph neural networks and reinforcement learning","volume":"182","author":"Liu","year":"2025","journal-title":"Comput. Oper. Res."},{"key":"10.1016\/j.rcim.2026.103364_bib0042","doi-asserted-by":"crossref","first-page":"4447","DOI":"10.3390\/electronics13224447","article-title":"HGNN\u2212BRFE: heterogeneous graph neural network model based on region feature extraction","volume":"13","author":"Zhao","year":"2024","journal-title":"Electronics"},{"key":"10.1016\/j.rcim.2026.103364_bib0043","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2020.106777","article-title":"SMT encodings for resource-constrained project scheduling problems","volume":"149","author":"Bofill","year":"2020","journal-title":"Comput. Ind. Eng."},{"key":"10.1016\/j.rcim.2026.103364_bib0044","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.111940","article-title":"Flexible job shop scheduling via deep reinforcement learning with meta-path-based heterogeneous graph neural network","volume":"296","author":"Wan","year":"2024","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.rcim.2026.103364_bib0045","doi-asserted-by":"crossref","first-page":"584","DOI":"10.3390\/machines12080584","article-title":"Solving flexible job-shop scheduling problem with heterogeneous graph neural network based on relation and deep reinforcement learning","volume":"12","author":"Tang","year":"2024","journal-title":"Machines"},{"key":"10.1016\/j.rcim.2026.103364_bib0046","doi-asserted-by":"crossref","DOI":"10.1155\/2015\/731734","article-title":"Imaging-duration embedded dynamic scheduling of earth observation satellites for emergent events","volume":"2015","author":"Niu","year":"2015","journal-title":"Math. Probl. Eng."},{"key":"10.1016\/j.rcim.2026.103364_bib0047","doi-asserted-by":"crossref","first-page":"8558","DOI":"10.1038\/s41598-023-34951-w","article-title":"Learning dispatching rules via novel genetic programming with feature selection in energy-aware dynamic job-shop scheduling","volume":"13","author":"Sitahong","year":"2023","journal-title":"Sci. Rep."},{"key":"10.1016\/j.rcim.2026.103364_bib0048","article-title":"CPSD2: a new approach for cyber-physical systems design and development","volume":"28","author":"Sampayo","year":"2022","journal-title":"J. Ind. Inf. Integr."},{"key":"10.1016\/j.rcim.2026.103364_bib0049","first-page":"33","article-title":"Learning to dispatch for job shop scheduling via deep reinforcement Learning","author":"Zhang","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.rcim.2026.103364_bib0050","doi-asserted-by":"crossref","first-page":"4420","DOI":"10.1109\/JIOT.2024.3485748","article-title":"End-to-end multitarget flexible job shop scheduling with deep reinforcement learning","volume":"12","author":"Wang","year":"2025","journal-title":"IEEE Internet Things J."},{"key":"10.1016\/j.rcim.2026.103364_bib0051","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.117796","article-title":"A multi-action deep reinforcement learning framework for flexible job-shop scheduling problem","volume":"205","author":"Lei","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.rcim.2026.103364_bib0052","series-title":"Proceedings of the International Conference on Learning Representations (ICLR)","article-title":"How powerful are graph neural networks?","author":"Xu","year":"2019"},{"key":"10.1016\/j.rcim.2026.103364_bib0053","series-title":"Proceedings of the International Conference on Learning Representations (ICLR)","article-title":"Graph attention networks","author":"Veli\u010dkovi\u0107","year":"2018"},{"key":"10.1016\/j.rcim.2026.103364_bib0054","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.rcim.2026.103364_bib0055","article-title":"Reinforcement learning for solving the vehicle routing problem","volume":"31","author":"Nazari","year":"2018","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.rcim.2026.103364_bib0056","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.asoc.2018.05.012","article-title":"Determining the optimal temperature parameter for Softmax function in reinforcement learning","volume":"70","author":"He","year":"2018","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.rcim.2026.103364_bib0057","series-title":"Proceedings of the International Conference on Learning Representations (ICLR)","article-title":"Proximal policy optimization algorithms","author":"Schulman","year":"2017"},{"key":"10.1016\/j.rcim.2026.103364_bib0058","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2024.105333","article-title":"Challenges and potential for human\u2013robot collaboration in timber prefabrication","volume":"160","author":"Yang","year":"2024","journal-title":"Autom. Constr."},{"key":"10.1016\/j.rcim.2026.103364_bib0059","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2023.109737","article-title":"Human-robot collaboration in assembly line balancing problems: review and research gaps","volume":"186","author":"Kheirabadi","year":"2023","journal-title":"Comput. Ind. Eng."},{"key":"10.1016\/j.rcim.2026.103364_bib0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.cor.2024.106874","article-title":"Multi objective optimization of human\u2013robot collaboration: a case study in aerospace assembly line","volume":"174","author":"H\u00e9mono","year":"2025","journal-title":"Comput. Oper. Res."},{"key":"10.1016\/j.rcim.2026.103364_bib0061","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1007\/s10845-022-02037-5","article-title":"Multi-agent reinforcement learning based on graph convolutional network for flexible job shop scheduling","volume":"35","author":"Jing","year":"2024","journal-title":"J. Intell. Manuf."},{"key":"10.1016\/j.rcim.2026.103364_bib0062","series-title":"Proceedings of the 2025 IEEE 21st International Conference on Automation Science and Engineering (CASE)","first-page":"650","article-title":"Group-based QMIX for multi-agent reinforcement learning","author":"Hong","year":"2025"},{"key":"10.1016\/j.rcim.2026.103364_bib0063","series-title":"Proceedings of the International Conference on Learning Representations (ICLR)","article-title":"QPLEX: duplex dueling multi-agent Q-learning","author":"Wang","year":"2021"},{"key":"10.1016\/j.rcim.2026.103364_bib0064","unstructured":"B. Peng, T. Rashid, C.A.S. de Witt, P.A. Kamienny, P.H.S. Torr, W. B\u00f6hmer, S. Whiteson, FACMAC: factored multi-agent centralised policy gradients, (2021). https:\/\/doi.org\/10.48550\/arXiv.2003.06709."},{"key":"10.1016\/j.rcim.2026.103364_bib0065","doi-asserted-by":"crossref","first-page":"1663","DOI":"10.3390\/electronics14081663","article-title":"Intelligent scheduling methods for optimisation of job shop scheduling problems in the manufacturing sector: a systematic review","volume":"14","author":"Momenikorbekandi","year":"2025","journal-title":"Electronics"},{"key":"10.1016\/j.rcim.2026.103364_bib0066","doi-asserted-by":"crossref","first-page":"142","DOI":"10.3390\/a17040142","article-title":"Dynamic events in the flexible job-shop scheduling problem: rescheduling with a hybrid metaheuristic algorithm","volume":"17","author":"Fuladi","year":"2024","journal-title":"Algorithms"},{"key":"10.1016\/j.rcim.2026.103364_bib0067","article-title":"Multilevel learning aided coevolutionary particle swarm optimization algorithm for multiobjective fuzzy flexible job shop scheduling problem","volume":"15","author":"Chen","year":"2025","journal-title":"Sci. Rep."}],"container-title":["Robotics and Computer-Integrated Manufacturing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0736584526001869?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0736584526001869?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T20:32:25Z","timestamp":1783024345000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0736584526001869"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2027,2]]},"references-count":67,"alternative-id":["S0736584526001869"],"URL":"https:\/\/doi.org\/10.1016\/j.rcim.2026.103364","relation":{},"ISSN":["0736-5845"],"issn-type":[{"value":"0736-5845","type":"print"}],"subject":[],"published":{"date-parts":[[2027,2]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Feature fusion-enhanced multi-agent reinforcement learning algorithm for human\u2013robot collaborative flexible job shop scheduling","name":"articletitle","label":"Article Title"},{"value":"Robotics and Computer-Integrated Manufacturing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.rcim.2026.103364","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"103364"}}