0000000000848637

AUTHOR

Zhong Yang

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Learning Automata Based Q-learning for Content Placement in Cooperative Caching

2019

An optimization problem of content placement in cooperative caching is formulated, with the aim of maximizing sum mean opinion score (MOS) of mobile users. Firstly, a supervised feed-forward back-propagation connectionist model based neural network (SFBC-NN) is invoked for user mobility and content popularity prediction. More particularly, practical data collected from GPS-tracker app on smartphones is tackled to test the accuracy of mobility prediction. Then, a learning automata-based Q-learning (LAQL) algorithm for cooperative caching is proposed, in which learning automata (LA) is invoked for Q-learning to obtain an optimal action selection in a random and stationary environment. It is p…

Signal Processing (eess.SP)Optimization problemLearning automatabusiness.industryComputer scienceMean opinion scoreQ-learningComputingMilieux_LEGALASPECTSOFCOMPUTING020206 networking & telecommunications02 engineering and technologycomputer.software_genreAction selectionIntelligent agentRecurrent neural networkFOS: Electrical engineering electronic engineering information engineering0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingQuality of experienceArtificial intelligenceElectrical and Electronic EngineeringElectrical Engineering and Systems Science - Signal ProcessingbusinessVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550computer
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