Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail

Vasilaki, E. orcid.org/0000-0003-3705-7070, Frémaux, N., Urbanczik, R. et al. (2 more authors) (2009) Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail. PLoS Computational Biology, 5 (12). e1000586. ISSN 1553-734X

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2009 Vasilaki et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Dates:
  • Published: 4 December 2009
  • Accepted: 30 October 2009
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 10 May 2016 09:34
Last Modified: 10 May 2016 09:34
Published Version: http://dx.doi.org/10.1371/journal.pcbi.1000586
Status: Published
Publisher: Public Library of Science
Refereed: Yes
Identification Number: https://doi.org/10.1371/journal.pcbi.1000586

Share / Export

Statistics