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Upper-Confidence-Bound Algorithms for Active Learning in Multi-armed Bandits · Study

WorkUpper-Confidence-Bound Algorithms for Active Learning in Multi-armed Bandits

Alexandra Carpentier2011

Work2011

Upper-Confidence-Bound Algorithms for Active Learning in Multi-armed Bandits

Alexandra Carpentier · Alessandro Lazaric · Mohammad Ghavamzadeh · Rémi Munos · Peter L. Auer

86 citations·0/0 files stored·Lecture notes in computer science

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Advanced Bandit Algorithms Research Reinforcement Learning in Robotics Machine Learning and Algorithms

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References

1972Theory of optimal experiments 1972Theory of Optimal Experiments.2009Exploration–exploitation tradeoff using variance estimates in multi-armed bandits 2010Best Arm Identification in Multi-Armed Bandits 2010Pure exploration in finitely-armed and continuous-armed bandits

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2013Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration 2012The strategic student approach for life-long exploration and learning 2013Gaussian Process Optimization with Mutual Information 2020Human complex exploration strategies are extended via noradrenaline-modulated heuristics

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Year2011

Typeother

Published2011-01-01

VenueLecture notes in computer science

ISSN-L0302-9743

Languageen

Citations86

Files0 public / 0

ShelfAdvanced Bandit Algorithms Research

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doi10.1007/978-3-642-24412-4_17

openalex_workW2102665362

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