Spiking Variational Policy Gradient for Brain Inspired Reinforcement Learning

Yang, Z. orcid.org/0000-0002-7908-9524, Guo, S., Fang, Y. et al. (2 more authors) (2024) Spiking Variational Policy Gradient for Brain Inspired Reinforcement Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. ISSN 0162-8828

Abstract

Metadata

Item Type: Article
Authors/Creators:
Copyright, Publisher and Additional Information:

© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Keywords: Reinforcement learning; reward-modulated spike-timing-dependent plasticity; spiking neural networks; variational policy gradient; winner-take-all circuit
Dates:
  • Published (online): 9 December 2024
  • Accepted: 29 November 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 31 Jan 2025 11:34
Last Modified: 31 Jan 2025 11:42
Status: Published online
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Identification Number: 10.1109/tpami.2024.3511936
Sustainable Development Goals:
  • Sustainable Development Goals: Goal 7: Affordable and Clean Energy
Open Archives Initiative ID (OAI ID):

Export

Statistics