[PDF][PDF] A new solution to distributed permutation flow shop scheduling problem based on NASH Q-Learning
JF Ren, CM Ye, Y Li - Advances in Production Engineering & …, 2021 - apem-journal.org
ABSTRACT ARTICLEINFO Aiming at Distributed Permutation Flow-shop Scheduling
Problems (DPFSPs), this study took the minimization of the maximum completion time of the …
Problems (DPFSPs), this study took the minimization of the maximum completion time of the …
[HTML][HTML] Applying multi-agent deep reinforcement learning for contention window optimization to enhance wireless network performance
This paper investigates the Contention Window (CW) optimization problem in multi-agent
scenarios, where the fully cooperative among mobile stations is considered. A partially …
scenarios, where the fully cooperative among mobile stations is considered. A partially …
Applying deep reinforcement learning to improve throughput and reduce collision rate in IEEE 802.11 networks
Abstract The effectiveness of Wi-Fi networks is greatly influenced by the optimization of
contention window (CW) parameters. Unfortunately, the conventional approach employed …
contention window (CW) parameters. Unfortunately, the conventional approach employed …
Reinforcement learning-based Wi-Fi contention window optimization
SJ Sheila de Cássia, MA Ouameur… - Journal of …, 2023 - jcis.emnuvens.com.br
The collision avoidance mechanism adopted by the IEEE 802.11 standard is not optimal.
The mechanism employs a binary exponential backoff (BEB) algorithm in the medium …
The mechanism employs a binary exponential backoff (BEB) algorithm in the medium …
Reinforcement Learning-based Wi-Fi Contention Window Optimization
SCS Cruz, MA Ouameur, FAP de Figueiredo - 2022 - preprints.org
The collision avoidance mechanism adopted by the IEEE 802.11 standard is not optimal.
The mechanism employs a binary exponential backoff (BEB) algorithm in the medium …
The mechanism employs a binary exponential backoff (BEB) algorithm in the medium …
Int-BEB: Enhanced Binary Exponential Backoff using Q-learning
N Zerguine - 2023 5th International Conference on Pattern …, 2023 - ieeexplore.ieee.org
Because of their development and success, MANETs are now preferred alternatives in many
fields of study and application. The IEEE 802.11 standard is the basis of most wireless …
fields of study and application. The IEEE 802.11 standard is the basis of most wireless …
Deep reinforcement learning-based contention window optimization for IEEE 802.11 networks
This study focuses on optimizing the contention window (CW) in IEEE 802.11 networks
using deep reinforcement learning (DRL) to enhance the effectiveness of the contention …
using deep reinforcement learning (DRL) to enhance the effectiveness of the contention …