A Bayesian Learning Automaton for Solving Two-Armed Bernoulli Bandit Problems

2008 ◽  
Author(s):  
Ole-Christoffer Granmo
Keyword(s):  
Bayesian Learning ◽  
Bandit Problems ◽  
Learning Automaton

INDEXABILITY OF BANDIT PROBLEMS WITH RESPONSE DELAYS

2010 ◽  
Vol 24 (3) ◽  
pp. 349-374 ◽  
Author(s):  
Felipe Caro ◽  
Onesun Steve Yoo
Keyword(s):  
Discrete Time ◽  
Bayesian Learning ◽  
The Other ◽  
Independent Random Variables ◽  
Important Class ◽  
Marginal Productivity ◽  
Bandit Problems ◽  
Theoretical Justification ◽  
State Spaces ◽  
Infinite State

This article considers an important class of discrete time restless bandits, given by the discounted multiarmed bandit problems with response delays. The delays in each period are independent random variables, in which the delayed responses do not cross over. For a bandit arm in this class, we use a coupling argument to show that in each state there is a unique subsidy that equates the pulling and nonpulling actions (i.e., the bandit satisfies the indexibility criterion introduced by Whittle (1988). The result allows for infinite or finite horizon and holds for arbitrary delay lengths and infinite state spaces. We compute the resulting marginal productivity indexes (MPI) for the Beta-Bernoulli Bayesian learning model, formulate and compute a tractable upper bound, and compare the suboptimality gap of the MPI policy to those of other heuristics derived from different closed-form indexes. The MPI policy performs near optimally and provides a theoretical justification for the use of the other heuristics.

Variational Bayesian Learning Theory

2019 ◽  
Author(s):  
Shinichi Nakajima ◽  
Kazuho Watanabe ◽  
Masashi Sugiyama
Keyword(s):  
Learning Theory ◽  
Bayesian Learning ◽  
Variational Bayesian

Blind Identification of Multichannel Systems Based on Sparse Bayesian Learning

2016 ◽  
Vol E99.B (12) ◽  
pp. 2614-2622 ◽  
Author(s):  
Kai ZHANG ◽  
Hongyi YU ◽  
Yunpeng HU ◽  
Zhixiang SHEN ◽  
Siyu TAO
Keyword(s):  
Bayesian Learning ◽  
Blind Identification ◽  
Sparse Bayesian Learning ◽  
Multichannel Systems
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