Fuzzy Motivations for Evolutionary Behavior Learning by a Mobile Robot
International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE),
Volume 4031,
pages 462--471,
doi: 10.1007/11779568_50
- Jun 2006
Associated documents :
In this paper we describe a fuzzy logic based approach for providing biologically based motivations to be used in evolutionary mobile robot learning. Takagi-Sugeno-Kang (TSK) fuzzy logic is used to motivate a small mobile robot to acquire complex behaviors and to perform environment recognition. This method is implemented and tested in behavior based navigation and action sequence based environment recognition tasks in a Khepera mobile robot simulator. Our fuzzy logic based motivation technique is shown as a simple and powerful method for a robot to acquire a diverse set of fit behaviors as well as providing an intuitive user interface framework.
@InProceedings{AFMNQ06,
author = {Arredondo, Tomás and Freund, Wolfgang and Muñoz, César and Navarro-Guerrero, Nicolás and Quirós, Fernando},
title = {Fuzzy Motivations for Evolutionary Behavior Learning by a Mobile Robot},
booktitle = {International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE)},
editors = {},
number = {},
volume = {4031},
pages = {462--471},
year = {2006},
month = {Jun},
publisher = {Springer-Verlag Berlin Heidelberg},
doi = {10.1007/11779568_50},
}