Title :
Using regression trees to learn action models
Author :
Balac, Natasha ; Gaines, Daniel M. ; Fisher, Doug
Author_Institution :
Dept. of Electr. Eng., Vanderbilt Univ., Nashville, TN, USA
Abstract :
Anyone who has ever driven a car on an icy road is aware of the impact the environment can have on our actions. In order to build effective plans, we must be aware of these environmental conditions and predict the effects they will have on our ability to act. We present an application of regression trees that allows a robot to learn action models through experience so that it can make similar predictions. We use this approach to allow a mobile robot to learn models to predict the effects of its navigation actions under various terrain conditions and use them in order to produce efficient plans
Keywords :
learning (artificial intelligence); mobile robots; path planning; trees (mathematics); action models; learning; mobile robot; planning; predictions; regression trees; robot navigation; terrain conditions; Lakes; Mobile robots; Navigation; Network address translation; Predictive models; Rain; Regression tree analysis; Roads; Testing; Tires;
Conference_Titel :
Systems, Man, and Cybernetics, 2000 IEEE International Conference on
Conference_Location :
Nashville, TN
Print_ISBN :
0-7803-6583-6
DOI :
10.1109/ICSMC.2000.886527
