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3441. Multi-armed bandits games
Invited abstract in session TB-6: Advancements of OR-Analytics in Statistics, Machine Learning and Data Science 13, stream Advancements of OR-analytics in statistics, machine learning and data science.
Tuesday, 10:30-12:00Room: 1013 (building: 202)
Authors (first author is the speaker)
| 1. | Kemal Gursoy
|
| MSIS, Rutgers University |
Abstract
A sequential optimization model, the multi-armed bandit problem, is concerned with optimal allocation of resources between competing activities, in order to generate the most likely benefits.
In this work, following the objective of a multi-armed bandit problem, we consider a game theoretic model to approach to an ensemble of multi-armed bandits.
Keywords
- Stochastic Optimization
- Game Theory
- Decision Theory
Status: accepted
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