{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T16:20:51Z","timestamp":1783009251105,"version":"3.54.5"},"reference-count":29,"publisher":"American Institute of Aeronautics and Astronautics (AIAA)","issue":"12","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52227811"],"award-info":[{"award-number":["52227811"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U23A20336"],"award-info":[{"award-number":["U23A20336"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100017055","name":"National Natural Science Foundation of China-Shandong Joint Fund","doi-asserted-by":"publisher","award":["ZR2024MF133"],"award-info":[{"award-number":["ZR2024MF133"]}],"id":[{"id":"10.13039\/100017055","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["arc.aiaa.org"],"crossmark-restriction":true},"short-container-title":["Journal of Aerospace Information Systems"],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:p>The increasing number of observation tasks in satellite operations has imposed higher demands on the scheduling timeliness and the efficiency of task completion, particularly in dense observation scenarios. For the Earth Observation Satellite Scheduling Problem, scheduling algorithms based on deep reinforcement learning face limitations, including low training efficiency and poor generalization capability. Therefore, this paper first establishes a mathematical model based on the Markov decision process for the 0\u20131 knapsack problem, considering the multiple constraints imposed on satellites. The objective of the model is to derive a strategy that maximizes satellite rewards. Subsequently, a meta-reinforcement learning (meta-RL) algorithm is employed to solve the satellite scheduling problem. Finally, after verifying the effectiveness of the algorithm, comparative experiments demonstrate that the meta-RL algorithm outperforms other comparable algorithms in handling large-scale problems. Additionally, the algorithm can map a small number of tasks to large-scale task planning, thereby improving its generalization capability.<\/jats:p>","DOI":"10.2514\/1.i011619","type":"journal-article","created":{"date-parts":[[2025,7,17]],"date-time":"2025-07-17T11:37:22Z","timestamp":1752752242000},"page":"1032-1042","update-policy":"https:\/\/doi.org\/10.2514\/aiaa_crossmarkpolicy","source":"Crossref","is-referenced-by-count":1,"title":["Task Scheduling for Single Satellite Observation Based on Meta-Reinforcement Learning"],"prefix":"10.2514","volume":"22","author":[{"given":"Zhi","family":"Li","sequence":"first","affiliation":[{"name":"Shandong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhibin","family":"Li","sequence":"additional","affiliation":[{"name":"Shandong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongjie","family":"Bai","sequence":"additional","affiliation":[{"name":"Shandong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1387","reference":[{"issue":"3","key":"r1","first-page":"84","volume":"18","author":"Gao H.","year":"2009","journal-title":"Spacecraft Engineering"},{"issue":"11","key":"r2","first-page":"130","volume":"27","author":"Deng B.","year":"2019","journal-title":"Computer Measurement & Control"},{"key":"r3","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.46.1.148.15134"},{"key":"r4","doi-asserted-by":"publisher","DOI":"10.1023\/B:JOSH.0000013053.32600.3c"},{"key":"r5","doi-asserted-by":"publisher","DOI":"10.1023\/A:1026488509554"},{"key":"r6","doi-asserted-by":"publisher","DOI":"10.1023\/A:1011203002719"},{"issue":"2","key":"r7","first-page":"213","volume":"35","author":"Lin W.","year":"2005","journal-title":"IEEE Transactions on Systems"},{"key":"r8","doi-asserted-by":"publisher","DOI":"10.1007\/s10589-008-9220-7"},{"issue":"5","key":"r9","first-page":"51","volume":"20","author":"Sun K.","year":"2013","journal-title":"Journal of Harbin Institute of Technology (New Series)"},{"issue":"3","key":"r11","first-page":"793","volume":"34","author":"Yan Z.","year":"2014","journal-title":"Systems Engineering-Theory & Practice"},{"issue":"35","key":"r12","first-page":"11","volume":"43","author":"Li J.","year":"2007","journal-title":"Computer Engineering and Applications"},{"key":"r13","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2003.815999"},{"key":"r14","doi-asserted-by":"publisher","DOI":"10.1016\/j.ast.2017.11.009"},{"issue":"2","key":"r15","first-page":"252","volume":"45","author":"Xiang S.","year":"2019","journal-title":"Acta Automatica Sinica"},{"issue":"12","key":"r16","first-page":"2715","volume":"47","author":"Du Y.","year":"2021","journal-title":"Acta Automatica Sinica"},{"issue":"7","key":"r17","first-page":"242","volume":"49","author":"Peng S.","year":"2022","journal-title":"Computer Science"},{"key":"r18","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2022.108242"},{"key":"r19","doi-asserted-by":"publisher","DOI":"10.2514\/1.I010754"},{"key":"r20","doi-asserted-by":"publisher","DOI":"10.1016\/j.cja.2018.12.018"},{"key":"r21","doi-asserted-by":"publisher","DOI":"10.3390\/rs13122377"},{"key":"r22","doi-asserted-by":"publisher","DOI":"10.2514\/1.I011209"},{"key":"r23","doi-asserted-by":"publisher","DOI":"10.1016\/j.asr.2022.10.024"},{"key":"r24","doi-asserted-by":"publisher","DOI":"10.1016\/j.cja.2023.10.011"},{"key":"r25","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-44668-0_13"},{"key":"r29","first-page":"1","volume":"25","author":"Cao Q.","year":"2024","journal-title":"IEEE Transactions on Automation Science and Engineering"},{"key":"r31","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(02)00228-9"},{"key":"r32","doi-asserted-by":"publisher","DOI":"10.1016\/j.physd.2019.132306"},{"key":"r34","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2022.3233358"},{"key":"r35","first-page":"1057","volume-title":"Advances in Neural Information Processing Systems","volume":"12","author":"Sutton R. 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