Quantum software engineering supremacy in intelligent robotics
Автор: Korenkov Vladimir, Reshetnikov Andrey, Ulyanov Sergey
Журнал: Сетевое научное издание «Системный анализ в науке и образовании» @journal-sanse
Статья в выпуске: 4, 2020 года.
Бесплатный доступ
A new approach for implementing quantum massive parallel computations is presented, using methods of circuit implementation of quantum algorithmic gates. Methods for designing fast quantum operators such as superposition, entanglement, and interference are considered. The presented methods allow you to reduce the number of actions that must be performed. The implementation is presented as a support tool for SW&HW supercomputer accelerator for modeling quantum algorithms. In particular, a new quantum-genetic and quantum-fuzzy inference algorithm for intelligent robotic control has been implemented. Also, a new method for performing Grover's inference without operations with the product is presented.
Quantum algorithm gate, hardware architecture, reduced quantum operations, classical efficient simulation, intelligent robotics
Короткий адрес: https://sciup.org/14122721
IDR: 14122721
Список литературы Quantum software engineering supremacy in intelligent robotics
- Ulyanov S.V. Self-organized robust intelligent control. LAP Lambert Academic Publishing, 2015.
- Ulyanov S.V. Quantum soft computing in control processes design: Quantum genetic algorithms and quantum neural network approaches. In: WAC (ISSCI') 2004 (5th Intern. Symp. on Soft Computing for Industry), Seville Spain, 2004;(17):99-104.
- Lahoz-Beltra R. Quantum genetic algorithms for computer scientists. Computers, 2016; 5(4):31-47.
- Ulyanov S.V. Self-organizing quantum robust control methods and systems for situations with uncertainty and risk. Patent US 8788450 B2, 2014.
- Liu Y., Feng S., Zhao Z., Ding E. Highly Efficient Human Action Recognition with Quantum Genetic Algorithm Optimized Support Vector Machine. ArXiv, abs/1711.09511, 2017.
- Fen W., Min L., Gang W., Xu J., Ren B., Wang G. Fault diagnosis approach of gearbox based on Support Vector Machine with improved bi-layers quantum genetic optimization. 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), Xi'an, 2016: 997-1002.
- Ivancova O.V., Korenkov V.V., Ulyanov S.V. Quantum software engineering. Moscow: Kurs, 2020.
- Ulyanov S.V., Ryabov N.V. The quantum genetic algorithm in the problems of intelligent control modeling and supercomputingSoftware & Systems, 2019;32(2):181-189.
- Ulyanov S.V., Ryabov N.V. Quantum simulator for modeling intelligent fuzzy control. Fuzzy Systems and Soft Computing. 2019;(1):19-33 (in Russ).
- DOI: 10.26456/fssc49 EDN: NGZCEQ
- Ulyanov S.V. Quantum Fuzzy Inference Based on Quantum Genetic Algorithm: Quantum Simulator in Intelligent Robotics. R. A. Aliev et al. (Eds.): ICSCCW 2019, AISC 1095, 2020;78-85.
- DOI: 10.1007/978-3-030-35249-3_9
