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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Reinforcement Learning for Cyber-Physical Systems: with Cybersecurity Case Studies

Reinforcement Learning for Cyber-Physical Systems: with Cybersecurity Case Studies

Li, Chong
Qiu, Meikang

Hardcover

General ComputersComputer Security

ISBN10: 1138543535
ISBN13: 9781138543539
Publisher: CRC Press
Published: Feb 4 2019
Pages: 256
Weight: 1.19
Height: 0.63 Width: 6.14 Depth: 9.21
Language: English

Reinforcement Learning for Cyber-Physical Systems: with Cybersecurity Case Studies was inspired by recent developments in the fields of reinforcement learning (RL) and cyber-physical systems (CPSs). Rooted in behavioral psychology, RL is one of the primary strands of machine learning. Different from other machine learning algorithms, such as supervised learning and unsupervised learning, the key feature of RL is its unique learning paradigm, i.e., trial-and-error. Combined with the deep neural networks, deep RL become so powerful that many complicated systems can be automatically managed by AI agents at a superhuman level. On the other hand, CPSs are envisioned to revolutionize our society in the near future. Such examples include the emerging smart buildings, intelligent transportation, and electric grids.

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