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Regret Bounds for Restless Markov Bandits · Study

WorkRegret Bounds for Restless Markov Bandits

Ronald Ortner2012

Work2012

Regret Bounds for Restless Markov Bandits

Ronald Ortner · Daniil Ryabko · Peter L. Auer · Rémi Munos

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

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Advanced Bandit Algorithms Research Reinforcement Learning in Robotics Optimization and Search Problems

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References

2002Finite-time Analysis of the Multiarmed Bandit Problem 2002The Nonstochastic Multiarmed Bandit Problem 1979Bandit Processes and Dynamic Allocation Indices 2012Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems 1988Restless bandits: activity allocation in a changing world 2010Near-optimal Regret Bounds for Reinforcement Learning 1987Asymptotically efficient allocation rules for the multiarmed bandit problem with multiple plays-Part I: I.I.D. rewards 2004Minimax policies for adversarial and stochastic bandits

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2018Recharging Bandits

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2014Regret bounds for restless Markov banditsarticle · 9 shared references 2012Learning in a Changing World: Restless Multiarmed Bandit With Unknown Dynamicsarticle · 6 shared references 2019Optimal Exploration–Exploitation in a Multi-armed Bandit Problem with Non-stationary Rewardsarticle · 6 shared references 2019Multi-Armed Bandits: Theory and Applications to Online Learning in Networksarticle · 6 shared references 2014From Bandits to Monte-Carlo Tree Search: The Optimistic Principle Applied to Optimization and Planningarticle · 5 shared references 20121 1 Online Learning of Rested and Restless Banditsarticle · 5 shared references

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Year2012

Typeother

Published2012-01-01

VenueLecture notes in computer science

ISSN-L0302-9743

Languageen

Citations37

Files0 public / 0

ShelfAdvanced Bandit Algorithms Research

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doi10.1007/978-3-642-34106-9_19

openalex_workW2149943599

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