Near-optimal Regret Bounds for Reinforcement Learning
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Standard
Near-optimal Regret Bounds for Reinforcement Learning. / Auer, Peter; Jaksch, Thomas; Ortner, Ronald.
Advances in neural information processing systems 21. MIT Press, 2009. p. 89-96.
Advances in neural information processing systems 21. MIT Press, 2009. p. 89-96.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Harvard
Auer, P, Jaksch, T & Ortner, R 2009, Near-optimal Regret Bounds for Reinforcement Learning. in Advances in neural information processing systems 21. MIT Press, pp. 89-96.
APA
Auer, P., Jaksch, T., & Ortner, R. (2009). Near-optimal Regret Bounds for Reinforcement Learning. In Advances in neural information processing systems 21 (pp. 89-96). MIT Press.
Vancouver
Auer P, Jaksch T, Ortner R. Near-optimal Regret Bounds for Reinforcement Learning. In Advances in neural information processing systems 21. MIT Press. 2009. p. 89-96
Author
Bibtex - Download
@inproceedings{e158eec351704acd85cea22126b0166a,
title = "Near-optimal Regret Bounds for Reinforcement Learning",
author = "Peter Auer and Thomas Jaksch and Ronald Ortner",
year = "2009",
language = "Deutsch",
pages = "89--96",
booktitle = "Advances in neural information processing systems 21",
publisher = "MIT Press",
address = "USA / Vereinigte Staaten",
}
RIS (suitable for import to EndNote) - Download
TY - GEN
T1 - Near-optimal Regret Bounds for Reinforcement Learning
AU - Auer, Peter
AU - Jaksch, Thomas
AU - Ortner, Ronald
PY - 2009
Y1 - 2009
M3 - Beitrag in Konferenzband
SP - 89
EP - 96
BT - Advances in neural information processing systems 21
PB - MIT Press
ER -
