A New Efficient Method for Refining the Reinforcement Learning Algorithm to Train Deep Q Agents for Reaching a Consensus in P2P Networks

A New Efficient Method for Refining the Reinforcement Learning Algorithm to Train Deep Q Agents for Reaching a Consensus in P2P Networks

The usage of distributed Peer-to-Peer (P2P) networks has been growing steadily for a reasonable period. Various applications rely on the infrastructure of P2P networks, where nodes communicate to accomplish a task without the need for a central authority. One of the significant challenges in P2P net...

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Bibliographic Details
Main Authors: Arafat Abu Mallouh, Zakariya Qawaqneh, Omar Abuzaghleh, Ahmad Al-Rababa'A
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Blockchain
consensus
deep reinforcement learning
DQN
P2P
Online Access:https://ieeexplore.ieee.org/document/10105270/

Internet

https://ieeexplore.ieee.org/document/10105270/

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