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Towards an Agent-Based Architecture using Deep Reinforcement Learning for Intelligent Internet of Things Applications.pdf (736.07 kB)
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Towards an Agent-Based Architecture using Deep Reinforcement Learning for Intelligent Internet of Things Applications.pdf

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posted on 20.04.2020 by Dhouha Ben Noureddine, Moez Krichen, Seifeddine Mechti, Tarik Nahhal, Wilfried Yves Hamilton Adoni
Internet of Things (IoT) is composed of many IoT devices connected throughout the Internet, that collect and share information to represent the environment. IoT is currently restructuring the actual manufacturing to smart manufacturing. However, inherent characteristics of IoT lead to a number of titanic challenges such as decentralization, weak interoperability, security, etc. The artificial intelligence provides opportunities to address IoT’s challenges, e.g the agent technology. This paper presents first an overview of ML and discusses some related work. Then, we briefly present the classic IoT architecture. Then we introduce our proposed Intelligent IoT (IIoT) architecture. We next concentrate on introducing the approach using multi-agent DRL in IIoT. Finally, in this promising field, we outline the open directions of future work.

History

Email Address of Submitting Author

moez.krichen@redcad.org

Submitting Author's Institution

ReDCAD Laboratory

Submitting Author's Country

Tunisia

Licence

Exports