Action Selection for Single- and Multi-Robot Tasks Using Cooperative Extended Kohonen Maps
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence. Pages 1505-1505.
Abstract
This paper presents an action selection framework based on an assemblage of self-organizing neural networks called Cooperative Extended Kohonen Maps. This framework encapsulates two features that significantly enhance a robot's action selection capability: self-organization in the continuous state and action spaces to provide smooth, efficient and fine motion control; action selection via the cooperation and competition of Extended Kohonen Maps to achieve more complex motion tasks. Qualitative and quantitative comparisons for single- and multirobot tasks show our framework can provide better action selection than do potential fields method.
@inproceedings{ijcai2003p252,
title = {Action Selection for Single- and Multi-Robot Tasks Using Cooperative Extended Kohonen Maps},
author = {Low, Kian Hsiang and Leow, Wee Kheng and Jr., Marcelo H. Ang},
booktitle = {Proceedings of the Eighteenth International Joint Conference on
Artificial Intelligence, {IJCAI-03}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Georg Gottlob},
pages = {1505--1505},
year = {2003},
url = {https://ijcai.org/proceedings/2003/252},
}
TY - CPAPER TI - Action Selection for Single- and Multi-Robot Tasks Using Cooperative Extended Kohonen Maps AU - Low, Kian Hsiang AU - Leow, Wee Kheng AU - Jr., Marcelo H. Ang T2 - Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03 PB - International Joint Conferences on Artificial Intelligence PY - 2003 SP - 1505 EP - 1505 UR - https://ijcai.org/proceedings/2003/252 ER -Copied
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