A Novel Clustering Algorithm Based on Quantum Games

Autor:	Li, Qiang, He, Yan, Jiang, Jing-ping
Rok vydání:	2008
Předmět:	Computer Science - Learning Computer Science - Artificial Intelligence Computer Science - Computer Vision and Pattern Recognition Computer Science - Computer Science and Game Theory Computer Science - Multiagent Systems Computer Science - Neural and Evolutionary Computing Quantum Physics
Zdroj:	2009 J. Phys. A: Math. Theor. 42 445303
Druh dokumentu:	Working Paper
DOI:	10.1088/1751-8113/42/44/445303
Popis:	Enormous successes have been made by quantum algorithms during the last decade. In this paper, we combine the quantum game with the problem of data clustering, and then develop a quantum-game-based clustering algorithm, in which data points in a dataset are considered as players who can make decisions and implement quantum strategies in quantum games. After each round of a quantum game, each player's expected payoff is calculated. Later, he uses a link-removing-and-rewiring (LRR) function to change his neighbors and adjust the strength of links connecting to them in order to maximize his payoff. Further, algorithms are discussed and analyzed in two cases of strategies, two payoff matrixes and two LRR functions. Consequently, the simulation results have demonstrated that data points in datasets are clustered reasonably and efficiently, and the clustering algorithms have fast rates of convergence. Moreover, the comparison with other algorithms also provides an indication of the effectiveness of the proposed approach. Comment: 19 pages, 5 figures, 5 tables
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/0812.0743 Zobrazit plný text záznamu View this record from Arxiv