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Review paper

Deep Reinforcement Learning for Internet of Things: A Comprehensive Survey

Volume: 23, Issue: 3, Pages: 1659 - 1692
Published: Jan 1, 2021
Abstract
The incumbent Internet of Things suffers from poor scalability and elasticity exhibiting in communication, computing, caching and control (4Cs) problems. The recent advances in deep reinforcement learning (DRL) algorithms can potentially address the above problems of IoT systems. In this context, this paper provides a comprehensive survey that overviews DRL algorithms and discusses DRL-enabled IoT applications. In particular, we first briefly...
Paper Details
Title
Deep Reinforcement Learning for Internet of Things: A Comprehensive Survey
Published Date
Jan 1, 2021
Volume
23
Issue
3
Pages
1659 - 1692
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