Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network
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Title
Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network
Authors
Keywords
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Journal
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
Volume 2018, Issue -, Pages 1-13
Publisher
Hindawi Limited
Online
2018-08-17
DOI
10.1155/2018/7560167
References
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- (2016) Guaning Chen et al. COMPUTER COMMUNICATIONS
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