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The one-leader and multi-follower Stackelberg game is adopted to analyze the mutual interference among multiple AEs, and the optimal transmit powers are proven to exist under the existing conditions. Following that, a mixed-strategy Stackelberg Equilibrium based on finite and discretized power set is also derived and a hierarchical Q-learning based power allocation algorithm (HQLA) is proposed to obtain the optimal power allocation strategy of the transmitter. Numerical results show that secrecy performance can be degraded severely by multiple AEs and verify the availability of the optimal power allocation strategy. Finally, the effect of the eavesdropping cost on the AE\u2019s attack mode strategies is also revealed.<\/jats:p>","DOI":"10.1155\/2020\/8825120","type":"journal-article","created":{"date-parts":[[2020,10,11]],"date-time":"2020-10-11T12:56:54Z","timestamp":1602421014000},"page":"1-15","source":"Crossref","is-referenced-by-count":11,"title":["Hierarchical Q-Learning Based UAV Secure Communication against Multiple UAV Adaptive Eavesdroppers"],"prefix":"10.1155","volume":"2020","author":[{"given":"Jue","family":"Liu","sequence":"first","affiliation":[{"name":"College of Communications Engineering, Army Engineering University of PLA, Nanjing 210007, China"},{"name":"School of Information Science and Engineering, Jinshen College of Nanjing Audit University, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nan","family":"Sha","sequence":"additional","affiliation":[{"name":"College of Communications Engineering, Army Engineering University of PLA, Nanjing 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