Application of reinforcement learning to wireless sensor networks: models and algorithms
Wireless sensor network (WSN) consists of a large number of sensors and sink nodes which are used to monitor events or environmental parameters, such as movement, temperature, humidity, etc. Reinforcement learning (RL) has been applied in a wide range of schemes in WSNs, such as cooperative communic...
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Veröffentlicht in: | Computing 2015-11, Vol.97 (11), p.1045-1075 |
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Sprache: | eng |
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