Individual subject evaluated difficulty of adjustable mazes generated using quantum annealing

Abstract

In this paper, 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 difficult 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.

arXiv comment20pages, 15figures

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Cited by in corpus (2)

• Subgradient Method using Quantum Annealing for Inequality-Constrained Binary Optimization Problems
• Efficient Construction of Feasible Solutions in Column Generation using Quantum Annealing