DocumentCode
2246466
Title
A reinforcement learning approach for QoS/QoE model identification
Author
Canale, S. ; Delli Priscoli, F. ; Monaco, S. ; Palagi, L. ; Suraci, V.
Author_Institution
Department of Computer, Control and Management Engineering “Antonio Ruberti” of the University of Rome “La Sapienza”, Rome, Italy
fYear
2015
fDate
28-30 July 2015
Firstpage
2019
Lastpage
2023
Abstract
In the last decade, researchers has focused their studies on the mathematical relation between the Quality of Service (QoS) and the user Quality of Experience (QoE). This paper investigates the problem of modelling the user QoE feedback in the next generation networks. The problem has been formulated and solved using a reinforcement learning technique. The proposed approach is innovative since it does not require an explicit knowledge of the mathematical model describing the network dynamics or the QoS/QoE relationship since it is learnt on-line. Simulation results shows that the proposed solution can adapt dynamically to the user behavior.
Keywords
Estimation; Internet; Irrigation; Learning (artificial intelligence); Mathematical model; Measurement; Quality of service;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2015 34th Chinese
Conference_Location
Hangzhou, China
Type
conf
DOI
10.1109/ChiCC.2015.7259941
Filename
7259941
Link To Document