Quantum Bandits

• URL: http://arxiv.org/abs/2002.06395v2
• Date: Tue, 22 Sep 2020 14:13:18 GMT
• Title: Quantum Bandits
• Authors: Balthazar Casal\'e, Giuseppe Di Molfetta, Hachem Kadri, Liva Ralaivola
• Abstract summary: 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.
• Score: 10.151012770913622
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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