Application of reinforcement learning in cognitive radio networks: Models and algorithms

10.1155/2014/209810

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Bibliographic Details
Main Authors:	Yau, K.-L.A, Poh, G.-S, Chien, S.F, Al-Rawi, H.A.A
Other Authors:	DEPT OF COMPUTER SCIENCE
Format:	Article
Published:	2020
Subjects:	article artificial intelligence cognition cognitive radio network decision making environmental factor learning learning algorithm reinforcement reward signal noise ratio spectrum wireless communication algorithm computer network human theoretical model Algorithms Artificial Intelligence Computer Communication Networks Humans Models, Theoretical Reinforcement (Psychology)
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/183716
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-183716
record_format	dspace
spelling	sg-nus-scholar.10635-1837162023-09-21T08:04:29Z Application of reinforcement learning in cognitive radio networks: Models and algorithms Yau, K.-L.A Poh, G.-S Chien, S.F Al-Rawi, H.A.A DEPT OF COMPUTER SCIENCE article artificial intelligence cognition cognitive radio network decision making environmental factor learning learning algorithm reinforcement reward signal noise ratio spectrum wireless communication algorithm artificial intelligence computer network human theoretical model Algorithms Artificial Intelligence Computer Communication Networks Humans Models, Theoretical Reinforcement (Psychology) 10.1155/2014/209810 Scientific World Journal 2014 209810 2020-11-19T07:18:17Z 2020-11-19T07:18:17Z 2014 Article Yau, K.-L.A, Poh, G.-S, Chien, S.F, Al-Rawi, H.A.A (2014). Application of reinforcement learning in cognitive radio networks: Models and algorithms. Scientific World Journal 2014 : 209810. ScholarBank@NUS Repository. https://doi.org/10.1155/2014/209810 23566140 https://scholarbank.nus.edu.sg/handle/10635/183716 Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ Unpaywall 20201031
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	article artificial intelligence cognition cognitive radio network decision making environmental factor learning learning algorithm reinforcement reward signal noise ratio spectrum wireless communication algorithm artificial intelligence computer network human theoretical model Algorithms Artificial Intelligence Computer Communication Networks Humans Models, Theoretical Reinforcement (Psychology)
spellingShingle	article artificial intelligence cognition cognitive radio network decision making environmental factor learning learning algorithm reinforcement reward signal noise ratio spectrum wireless communication algorithm artificial intelligence computer network human theoretical model Algorithms Artificial Intelligence Computer Communication Networks Humans Models, Theoretical Reinforcement (Psychology) Yau, K.-L.A Poh, G.-S Chien, S.F Al-Rawi, H.A.A Application of reinforcement learning in cognitive radio networks: Models and algorithms
description	10.1155/2014/209810
author2	DEPT OF COMPUTER SCIENCE
author_facet	DEPT OF COMPUTER SCIENCE Yau, K.-L.A Poh, G.-S Chien, S.F Al-Rawi, H.A.A
format	Article
author	Yau, K.-L.A Poh, G.-S Chien, S.F Al-Rawi, H.A.A
author_sort	Yau, K.-L.A
title	Application of reinforcement learning in cognitive radio networks: Models and algorithms
title_short	Application of reinforcement learning in cognitive radio networks: Models and algorithms
title_full	Application of reinforcement learning in cognitive radio networks: Models and algorithms
title_fullStr	Application of reinforcement learning in cognitive radio networks: Models and algorithms
title_full_unstemmed	Application of reinforcement learning in cognitive radio networks: Models and algorithms
title_sort	application of reinforcement learning in cognitive radio networks: models and algorithms
publishDate	2020
url	https://scholarbank.nus.edu.sg/handle/10635/183716
_version_	1779153130990075904

Application of reinforcement learning in cognitive radio networks: Models and algorithms

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