@inproceedings{141d5d7e13db42949eca66b60f75e450,
title = "A Novel Ant Clustering Algorithm Based on Cellular Automata",
abstract = "Based on the principle of cellular automata in artificial life, an artificial Ants Sleeping Model (ASM) and an ant algorithm for cluster analysis (A4C) are presented. Inspired by the behaviors of gregarious ant colonies, we use the ant agent to represent data object. In ASM, each ant has two states: sleeping state and active state. The ant's state is controlled by a function of the ant's fitness to the environment it locates and a probability for the ants becoming active. The state of an ant is determined only by its local information. By moving dynamically, the ants form different subgroups adoptively, and hence the data objects they represent are clustered. Experimental results show that the A4C algorithm on ASM is significantly better than other clustering methods in terms of both speed and quality. It is adaptive, robust and efficient, achieving high autonomy, simplicity and efficiency.",
keywords = "Ant colony algorithm, Ants Sleeping Model, Cellular automata, Swarm intelligence",
author = "Ling Chen and Xiaohua Xu and Yixin Chen and Ping He",
year = "2004",
language = "English",
isbn = "0769521010",
series = "Proceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004",
pages = "148--154",
editor = "N. Zhong and J. Bradshaw and S.K. Pal and D. Talia and J. Liu and N. Cercone",
booktitle = "Proceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Systems. IAT 2004",
note = "Proceedings - IEEE/WIC/ACM International Conference on Intelligent Agent Technology. IAT 2004 ; Conference date: 20-09-2004 Through 24-09-2004",
}