z-logo
open-access-imgOpen Access
Correction: Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail
Author(s) -
Eleni Vasilaki,
Nicolas Frémaux,
Robert Urbanczik,
Walter Senn,
Wulfram Gerstner
Publication year - 2009
Publication title -
plos computational biology/plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/annotation/307ea250-3792-4ceb-b905-162d86c96baf
Subject(s) - reinforcement learning , spike (software development) , computer science , state space , action (physics) , artificial intelligence , reinforcement , space (punctuation) , mathematics , statistics , physics , psychology , social psychology , software engineering , quantum mechanics , operating system

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here