A Deep Reinforcement Learning Approach for Composing Moving IoT Services
We develop a novel framework for efficiently and effectively discovering crowdsourced services that move in close proximity to a user over a period of time. We introduce a moving crowdsourced service model which is modelled as a moving region. We propose a deep reinforcement learning-based compositi...
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Veröffentlicht in: | IEEE transactions on services computing 2022-09, Vol.15 (5), p.2538-2550 |
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Sprache: | eng |
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