On suitability of the reinforcement learning methodology in dynamic, heterogeneous, self-optimizing networks

dc.contributor.author	Rovcanin, Milos
dc.contributor.author	De Poorter, Eli
dc.contributor.author	Moerman, Ingrid
dc.contributor.author	Demeester, Piet
dc.contributor.imecauthor	De Poorter, Eli
dc.contributor.imecauthor	Moerman, Ingrid
dc.contributor.imecauthor	Demeester, Piet
dc.contributor.orcidimec	De Poorter, Eli::0000-0002-0214-5751
dc.contributor.orcidimec	Moerman, Ingrid::0000-0003-2377-3674
dc.contributor.orcidimec	Demeester, Piet::0000-0003-2810-3899
dc.date.accessioned	2021-10-21T11:34:52Z
dc.date.available	2021-10-21T11:34:52Z
dc.date.embargo	9999-12-31
dc.date.issued	2013
dc.identifier.uri	https://imec-publications.be/handle/20.500.12860/23019
dc.identifier.url	http://rd.springer.com/chapter/10.1007%2F978-3-642-40316-3_15#
dc.source.beginpage	162
dc.source.conference	13th International Conference on Next Generation Wired/Wireless Advanced Networking - NEW2AN
dc.source.conferencedate	28/08/2013
dc.source.conferencelocation	Sint-Petersburg Russia
dc.source.endpage	175
dc.title	On suitability of the reinforcement learning methodology in dynamic, heterogeneous, self-optimizing networks
dc.type	Proceedings paper
dspace.entity.type	Publication
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