DocumentCode
2667704
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
Volume
5
fYear
2000
fDate
2000
Firstpage
3378
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 2000 IEEE International Conference on
Conference_Location
Nashville, TN
ISSN
1062-922X
Print_ISBN
0-7803-6583-6
Type
conf
DOI
10.1109/ICSMC.2000.886527
Filename
886527
Link To Document