Quantum Bandits
Machine Learning
2020-09-23 v2 Artificial Intelligence
Quantum Physics
Machine Learning
Abstract
We consider the quantum version of the bandit problem known as {\em best arm identification} (BAI). We first propose a quantum modeling of the BAI problem, which assumes that both the learning agent and the environment are quantum; we then propose an algorithm based on quantum amplitude amplification to solve BAI. We formally analyze the behavior of the algorithm on all instances of the problem and we show, in particular, that it is able to get the optimal solution quadratically faster than what is known to hold in the classical case.
Cite
@article{arxiv.2002.06395,
title = {Quantum Bandits},
author = {Balthazar Casalé and Giuseppe Di Molfetta and Hachem Kadri and Liva Ralaivola},
journal= {arXiv preprint arXiv:2002.06395},
year = {2020}
}
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