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Discrete-to-deep reinforcement learning methods

journal contribution

posted on 2022-01-01, 00:00 authored by B Kurniawan, P Vamplew, M Papasimeon, Richard DazeleyRichard Dazeley, C Foale

Discrete-to-deep reinforcement learning methods

History

Journal

Neural Computing and Applications

Volume

34

Issue

3

Pagination

1713 - 1733

Publisher

Springer

Location

Berlin, Germany

Publisher DOI

https://doi.org/10.1007/s00521-021-06270-6

ISSN

0941-0643

eISSN

1433-3058

Language

English

Author URL

http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000702618200001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a045e4b2bb1f2b747c68c720ec8913b7

Publication classification

C1 Refereed article in a scholarly journal

Usage metrics

Research Publications

Categories

Artificial Intelligence and Image Processing

Keywords

Actor-critic Computer Science Computer Science, Artificial Intelligence DQN Neural network Reinforcement learning Science & Technology Supervised learning Technology

Licence

All Rights Reserved

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