@inproceedings{e0ab6abc6cef4587b3752f7c63c31dcd,
title = "Creating learning sets for control systems using an evolutionary method",
abstract = "The acquisition of the knowledge which is useful for developing of artificial intelligence systems is still a problem. We usually ask experts, apply historical data or reap the results of mensuration from a real simulation of the object. In the paper we propose a new algorithm to generate a representative training set. The algorithm is based on analytical or discrete model of the object with applied the k-nn and genetic algorithms. In this paper it is presented the control case of the issue illustrated by well known truck backer-upper problem. The obtained training set can be used for training many AI systems such as neural networks, fuzzy and neuro-fuzzy architectures and k-nn systems.",
keywords = "control system, genetic algorithm, training data acquisition",
author = "Marcin Gabryel and Marcin Wo{\'z}niak and \{K. Nowicki\}, Robert",
year = "2012",
doi = "10.1007/978-3-642-29353-5\_24",
language = "English",
isbn = "9783642293528",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "206--213",
booktitle = "Swarm and Evolutionary Computation - International Symposia, SIDE 2012 and EC 2012, Held in Conjunction with ICAISC 2012, Proceedings",
note = "Symposium on Swarm Intelligence and Differential Evolution, SIDE 2012 and Symposium on Evolutionary Computation, EC 2012, Held in Conjunction with 11th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2012 ; Conference date: 29-04-2012 Through 03-05-2012",
}