Towards an Agent-Based Architecture using Deep Reinforcement Learning
for Intelligent Internet of Things Applications
Abstract
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.