Individual subject evaluated difficulty of adjustable mazes generated using quantum annealing
In this study, the maze generation using quantum annealing is proposed. We reformulate a standard algorithm to generate a maze into a specific form of a quadratic unconstrained binary optimization problem suitable for the input of the quantum annealer. To generate more difficulty mazes, we introduce...
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Published in | Frontiers in computer science (Lausanne) Vol. 5 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Frontiers Media S.A
07.12.2023
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Subjects | |
Online Access | Get full text |
ISSN | 2624-9898 2624-9898 |
DOI | 10.3389/fcomp.2023.1285962 |
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Abstract | In this study, the maze generation using quantum annealing is proposed. We reformulate a standard algorithm to generate a maze into a specific form of a quadratic unconstrained binary optimization problem suitable for the input of the quantum annealer. To generate more difficulty mazes, we introduce an additional cost function
Q
update
to increase the difficulty. The difficulty of the mazes was evaluated by the time to solve the maze of 12 human subjects. To check the efficiency of our scheme to create the maze, we investigated the time-to-solution of a quantum processing unit, classical computer, and hybrid solver. The results show that
Q
update
generates difficult mazes tailored to the individual. Furthermore, it show that the quantum processing unit is more efficient at generating mazes than other solvers. Finally, we also present applications how our results could be used in the future. |
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AbstractList | In this study, the maze generation using quantum annealing is proposed. We reformulate a standard algorithm to generate a maze into a specific form of a quadratic unconstrained binary optimization problem suitable for the input of the quantum annealer. To generate more difficulty mazes, we introduce an additional cost function Qupdate to increase the difficulty. The difficulty of the mazes was evaluated by the time to solve the maze of 12 human subjects. To check the efficiency of our scheme to create the maze, we investigated the time-to-solution of a quantum processing unit, classical computer, and hybrid solver. The results show that Qupdate generates difficult mazes tailored to the individual. Furthermore, it show that the quantum processing unit is more efficient at generating mazes than other solvers. Finally, we also present applications how our results could be used in the future. In this study, the maze generation using quantum annealing is proposed. We reformulate a standard algorithm to generate a maze into a specific form of a quadratic unconstrained binary optimization problem suitable for the input of the quantum annealer. To generate more difficulty mazes, we introduce an additional cost function Q update to increase the difficulty. The difficulty of the mazes was evaluated by the time to solve the maze of 12 human subjects. To check the efficiency of our scheme to create the maze, we investigated the time-to-solution of a quantum processing unit, classical computer, and hybrid solver. The results show that Q update generates difficult mazes tailored to the individual. Furthermore, it show that the quantum processing unit is more efficient at generating mazes than other solvers. Finally, we also present applications how our results could be used in the future. |
Author | Okamura, Keita Ohzeki, Masayuki Yoshihara, Takuma Ishikawa, Yuto |
Author_xml | – sequence: 1 givenname: Yuto surname: Ishikawa fullname: Ishikawa, Yuto – sequence: 2 givenname: Takuma surname: Yoshihara fullname: Yoshihara, Takuma – sequence: 3 givenname: Keita surname: Okamura fullname: Okamura, Keita – sequence: 4 givenname: Masayuki surname: Ohzeki fullname: Ohzeki, Masayuki |
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Title | Individual subject evaluated difficulty of adjustable mazes generated using quantum annealing |
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