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The problem is modeled as a Markov decision process, including the well-designed state features, rewards, and actions based on different rescheduling methods. The policy is trained by the proximal policy optimization algorithm. At last, numerical results are provided to demonstrate the effectiveness and superiority of the proposed approach.<\/jats:p>","DOI":"10.1007\/s40747-024-01365-8","type":"journal-article","created":{"date-parts":[[2024,3,5]],"date-time":"2024-03-05T10:02:42Z","timestamp":1709632962000},"page":"4329-4349","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A predictive-reactive strategy for flight test task scheduling with aircraft grounding"],"prefix":"10.1007","volume":"10","author":[{"given":"Bei","family":"Tian","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9259-6790","authenticated-orcid":false,"given":"Gang","family":"Xiao","sequence":"additional","affiliation":[]},{"given":"Yu","family":"Shen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,3,5]]},"reference":[{"key":"1365_CR1","unstructured":"Stoliker FN (1995) Introduction to flight test engineering. 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