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The cooperative guidance process is first analyzed for multiple aircraft by formulating flight scenarios using multiagent Markov game theory and solving it by machine learning algorithm. Furthermore, a self\u2010learning framework is established by using the actor\u2010critic model, which is proposed to train collision avoidance decision\u2010making neural networks. To achieve higher scalability, the neural network is customized to incorporate long short\u2010term memory networks, and a coordination strategy is given. Additionally, a simulator suitable for multiagent high\u2010density route scene is designed for validation, in which all UAVs run the proposed algorithm onboard. Simulated experiment results from several case studies show that the real\u2010time guidance algorithm can reduce the collision probability of multiple UAVs in flight effectively even with a large number of aircraft.<\/jats:p>","DOI":"10.1155\/2021\/8818013","type":"journal-article","created":{"date-parts":[[2021,1,19]],"date-time":"2021-01-19T03:35:32Z","timestamp":1611027332000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Reinforcement Learning\u2010Based Collision Avoidance Guidance Algorithm for Fixed\u2010Wing UAVs"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7229-0834","authenticated-orcid":false,"given":"Yu","family":"Zhao","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2840-9820","authenticated-orcid":false,"given":"Jifeng","family":"Guo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0349-9869","authenticated-orcid":false,"given":"Chengchao","family":"Bai","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8685-9080","authenticated-orcid":false,"given":"Hongxing","family":"Zheng","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,1,18]]},"reference":[{"doi-asserted-by":"publisher","key":"e_1_2_10_1_2","DOI":"10.1016\/j.cja.2019.03.026"},{"doi-asserted-by":"publisher","key":"e_1_2_10_2_2","DOI":"10.1155\/2020\/4757381"},{"doi-asserted-by":"publisher","key":"e_1_2_10_3_2","DOI":"10.1109\/access.2018.2885003"},{"doi-asserted-by":"publisher","key":"e_1_2_10_4_2","DOI":"10.1155\/2018\/8420294"},{"doi-asserted-by":"crossref","unstructured":"AlzugarayI.andSanfeliuA. 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