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» A structured multiarmed bandit problem and the greedy policy
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CDC
2009
IEEE
123views Control Systems» more  CDC 2009»
15 years 2 months ago
On the myopic policy for a class of restless bandit problems with applications in dynamic multichannel access
We consider a class of restless multi-armed bandit problems that arises in multi-channel opportunistic communications, where channels are modeled as independent and stochastically...
Keqin Liu, Qing Zhao
TSP
2010
14 years 4 months ago
Distributed learning in multi-armed bandit with multiple players
We formulate and study a decentralized multi-armed bandit (MAB) problem. There are distributed players competing for independent arms. Each arm, when played, offers i.i.d. reward a...
Keqin Liu, Qing Zhao
ICASSP
2010
IEEE
14 years 9 months ago
Distributed learning in cognitive radio networks: Multi-armed bandit with distributed multiple players
—We consider a cognitive radio network with distributed multiple secondary users, where each user independently searches for spectrum opportunities in multiple channels without e...
Keqin Liu, Qing Zhao
AGI
2011
14 years 1 months ago
Reinforcement Learning and the Bayesian Control Rule
We present an actor-critic scheme for reinforcement learning in complex domains. The main contribution is to show that planning and I/O dynamics can be separated such that an intra...
Pedro Alejandro Ortega, Daniel Alexander Braun, Si...
COLT
2003
Springer
15 years 2 months ago
Lower Bounds on the Sample Complexity of Exploration in the Multi-armed Bandit Problem
We consider the Multi-armed bandit problem under the PAC (“probably approximately correct”) model. It was shown by Even-Dar et al. [5] that given n arms, it suffices to play th...
Shie Mannor, John N. Tsitsiklis