Near-optimal Regret Bounds for Reinforcement Learning

Research output: Chapter in Book/Report/Conference proceedingConference 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.

Research output: Chapter in Book/Report/Conference proceedingConference 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

Auer, Peter ; Jaksch, Thomas ; Ortner, Ronald. / Near-optimal Regret Bounds for Reinforcement Learning. Advances in neural information processing systems 21. MIT Press, 2009. pp. 89-96

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 -