Deep imitation learning: the impact of depth on policy performance Kebria, Parham M, Khosravi, Abbas, Salaken, Syed Moshfeq, Hossain, Ibrahim, Kabir, Hussain Mohammed Dipu, Koohestani, Afsaneh, Alizadehsani, Roohallah and Nahavandi, Saeid 2018, Deep imitation learning: the impact of depth on policy performance, in ICONIP 2018 : Proceedings of the 25th International Conference on Neural Information Processing, Springer, Cham, Switzerland, pp. 172-181, doi: 10.1007/978-3-030-04167-0_16. Attached Files Name Description MIMEType Size Downloads Title Deep imitation learning: the impact of depth on policy performance Author(s) Kebria, Parham M Khosravi, Abbas orcid.org/0000-0001-6927-0744 Salaken, Syed Moshfeq orcid.org/0000-0001-8632-2665 Hossain, Ibrahim Kabir, Hussain Mohammed Dipu orcid.org/0000-0002-3395-1772 Koohestani, Afsaneh Alizadehsani, Roohallah Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Conference name Asia Pacific Neural Network Society. Conference (25th : 2018 : Siem Reap, Cambodia) Conference location Siem Reap, Cambodia Conference dates 2018/12/13 - 2018/12/16 Title of proceedings ICONIP 2018 : Proceedings of the 25th International Conference on Neural Information Processing Editor(s) Cheng, Long Leung, Andrew Chi Sing Ozawa, Seiichi Publication date 2018 Series Asia Pacific Neural Network Society Conference Start page 172 End page 181 Total pages 10 Publisher Springer Place of publication Cham, Switzerland Keyword(s) Autonomous vehicle Imitation learning Simulation Depth ISBN 9783030041663 ISSN 0302-9743 1611-3349 Language eng DOI 10.1007/978-3-030-04167-0_16 Field of Research 08 Information and Computing Sciences HERDC Research category E1 Full written paper - refereed Copyright notice ©2018, Springer Nature Switzerland AG Persistent URL http://hdl.handle.net/10536/DRO/DU:30123289 Document type: Conference Paper Collections: Centre for Intelligent Systems Research GTP Research Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Tue, 25 Jun 2019, 14:55:06 EST Tue, 25 Jun 2019, 14:55:52 EST Wed, 26 Jun 2019, 05:02:13 EST Wed, 26 Jun 2019, 06:03:29 EST Fri, 28 Jun 2019, 11:25:20 EST Fri, 28 Jun 2019, 11:30:36 EST Fri, 28 Jun 2019, 11:31:23 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 1 times in Scopus Search Google Scholar Access Statistics: 67 Abstract Views, 4 File Downloads  -  Detailed Statistics Created: Tue, 25 Jun 2019, 14:55:52 EST

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