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In this paper, an end\u2010to\u2010end UAV intelligent mission planning method based on deep reinforcement learning (DRL) is proposed to solve the shortcomings of the traditional intelligent optimization algorithm, such as relying on simple, static, low\u2010dimensional scenarios, and poor scalability. Specifically, the suppression of enemy air defense (SEAD) mission planning is described as a sequential decision\u2010making problem and formalized as a Markov decision process (MDP). Then, the SEAD intelligent planning model based on the proximal policy optimization (PPO) algorithm is established and a general intelligent planning architecture is proposed. Furthermore, three policy training tricks, i.e., domain randomization, maximizing policy entropy, and underlying network parameter sharing, are introduced to improve the learning performance and generalizability of PPO. Experiments results show that the model in this work is efficient and stable, and can be adapted to the unknown continuous high\u2010dimensional environment. It can be concluded that the UAV intelligent mission planning model based on DRL has powerful intelligent planning performance, and provides a new idea for researching UAV autonomy.<\/jats:p>","DOI":"10.1155\/2022\/3551508","type":"journal-article","created":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T13:20:40Z","timestamp":1648732840000},"update-policy":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Deep Reinforcement Learning for UAV Intelligent Mission Planning"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/orcid.org\/0000-0003-4618-5955","authenticated-orcid":false,"given":"Longfei","family":"Yue","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/orcid.org\/0000-0002-6014-5303","authenticated-orcid":false,"given":"Rennong","family":"Yang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/orcid.org\/0000-0001-9347-6224","authenticated-orcid":false,"given":"Ying","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/orcid.org\/0000-0003-0174-6464","authenticated-orcid":false,"given":"Lixin","family":"Yu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/orcid.org\/0000-0002-2816-8329","authenticated-orcid":false,"given":"Zhuangzhuang","family":"Wang","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2022,3,31]]},"reference":[{"key":"e_1_2_11_1_2","first-page":"593","article-title":"Overview of air vehicle mission planning techniques","volume":"35","author":"Shen L.","year":"2014","journal-title":"Acta Aeronautica et Astronautica Sinica"},{"key":"e_1_2_11_2_2","unstructured":"Joint mission planning system Joint mission planning system 2020 https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/www.globalsecurity.org\/military\/systems\/aircraft\/jmps.htm."},{"key":"e_1_2_11_3_2","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1820\/1\/012180"},{"key":"e_1_2_11_4_2","first-page":"1074","article-title":"Tactic maneuver planning of loft delivery of laser-guided bomb with no offset","volume":"38","author":"Zhang Y.","year":"2016","journal-title":"Systems Engineering and Electronics"},{"key":"e_1_2_11_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/tevc.2007.892759"},{"key":"e_1_2_11_6_2","doi-asserted-by":"crossref","unstructured":"DarrahM.andNilandW. 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