Bandit problems with side observations

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Abstract

An extension of the traditional two-armed bandit problem is considered, in which the decision maker has access to some side information before deciding which arm to pull. At each time t, before making a selection, the decision maker is able to observe a random variable Xt that provides some information on the rewards to be obtained. The focus is on finding uniformly good rules (that minimize the growth rate of the inferior sampling time) and on quantifying how much the additional information helps. Various settings are considered and for each setting, lower bounds on the achievable inferior sampling time are developed and asymptotically optimal adaptive schemes achieving these lower bounds are constructed.

Original languageEnglish (US)
Pages (from-to)338-355
Number of pages18
JournalIEEE Transactions on Automatic Control
Volume50
Issue number3
DOIs
StatePublished - Mar 1 2005

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

Keywords

  • Adaptive
  • Allocation rule
  • Asymptotic
  • Efficient
  • Inferior sampling time
  • Side information
  • Two-armed bandit

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