Quantum Mechanics Helps in Learning for More Intelligent Robots

2005/06/18 by Dao-Yi Dong, Daoyi Dong, Chun-Lin Chen +5
Computer Science · Physics and Astronomy · #Computability, Logic, AI Algorithms #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #quant-ph

paper · pdf · doi:10.1088/0256-307x/23/7/010

published as Chinese Physics Letters, 2006,23(7):1691-1694 · 9 pages, 2 figures

arxiv created 2005/06/18 · openalex publication_date 2006/06/28 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/30

Abstract

A learning algorithm based on the state superposition principle is presented. The theoretical analysis shows that the needed fundamental transformations to realize this algorithm are the same as those needed in the Grover algorithm and are within current state-of-the-art technology. The simulated experiment shows that the quantum learning algorithm can help robots to learn faster and to become more intelligent.

Citations

• Control of non-controllable quantum systems: a quantum control algorithm based on Grover iteration
• Quantum mechanical computers
• Tight Bounds on Quantum Searching
• Quantum theory, the Church–Turing principle and the universal quantum computer
• Simulating physics with computers
• Reinforcement Learning: An Introduction