Efficient learning by implicit exploration in bandit problems with side observations - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2014

Efficient learning by implicit exploration in bandit problems with side observations

Tomáš Kocák
  • Function : Author
  • PersonId : 955512
Gergely Neu
  • Function : Author
  • PersonId : 961171
Michal Valko
Rémi Munos
  • Function : Author
  • PersonId : 836863

Abstract

We consider online learning problems under a a partial observability model capturing situations where the information conveyed to the learner is between full information and bandit feedback. In the simplest variant, we assume that in addition to its own loss, the learner also gets to observe losses of some other actions. The revealed losses depend on the learner's action and a directed observation system chosen by the environment. For this setting, we propose the first algorithm that enjoys near-optimal regret guarantees without having to know the observation system before selecting its actions. Along similar lines, we also define a new partial information setting that models online combinatorial optimization problems where the feedback received by the learner is between semi-bandit and full feedback. As the predictions of our first algorithm cannot be always computed efficiently in this setting, we propose another algorithm with similar properties and with the benefit of always being computationally efficient, at the price of a slightly more complicated tuning mechanism. Both algorithms rely on a novel exploration strategy called implicit exploration, which is shown to be more efficient both computationally and information-theoretically than previously studied exploration strategies for the problem.
Fichier principal
Vignette du fichier
kocak2014efficient.pdf (409.14 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01079351 , version 1 (01-11-2014)
hal-01079351 , version 2 (03-11-2014)

Identifiers

  • HAL Id : hal-01079351 , version 2

Cite

Tomáš Kocák, Gergely Neu, Michal Valko, Rémi Munos. Efficient learning by implicit exploration in bandit problems with side observations. Neural Information Processing Systems, Dec 2014, Montréal, Canada. ⟨hal-01079351v2⟩
446 View
305 Download

Share

Gmail Facebook X LinkedIn More