Using regression trees to learn action models

被引：0

作者：

Balac, N ^{[1
]}

Gaines, DM ^{[1
]}

Fisher, D ^{[1
]}

机构：

[1] Vanderbilt Univ, Dept Elect Engn & Comp Sci, Nashville, TN 37240 USA

来源：

SMC 2000 CONFERENCE PROCEEDINGS: 2000 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN & CYBERNETICS, VOL 1-5 | 2000年

关键词：

robotics; navigation; planning; learning;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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. In this paper, 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.

引用

页码：3378 / 3383

页数：6

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