@inproceedings{37348f2db37b47c8bc2685a80737d783,
title = "A bayesian optimization algorithm for UAV path planning",
abstract = "A Bayesian optimization algorithm (BOA) for unmanned aerial vehicle (UAV) path planning is presented, which involves choosing path representation and designing appropriate metric to measure the quality of the constructed network. Unlike our previous work in which genetic algorithm (GA) was used to implement implicit learning, the learning in the proposed algorithm is explicit, and the BOA is applied to implement such explicit learning by building a Bayesian network of the joint distribution of solutions. Experimental results demonstrate that this approach can overcome some drawbacks of other path planning algorithms. It is also suggested that the learning mechanism in the proposed approach might be suitable for other multivariate encoding problems.",
keywords = "Bayesian network, Bayesian optimization algorithm, Genetic algorithm, Path planning, UAV",
author = "X. Fu and X. Gao and D. Chen",
year = "2005",
doi = "10.1007/0-387-23152-8_29",
language = "英语",
isbn = "038723151X",
series = "IFIP Advances in Information and Communication Technology",
publisher = "Springer New York LLC",
pages = "227--232",
booktitle = "Intelligent Information Processing II - IFIP TC12/WG12.3 International Conference on Intelligent Information Processing, IIP 2004",
note = "IFIP TC12/WG12.3 International Conference on Intelligent Information Processing, IIP 2004 ; Conference date: 21-10-2004 Through 23-10-2004",
}