A Game Playing Robot that Can Learn From Experience

被引：0
|
作者：
El-Azim, Raafat Ahmed Abd [1 ]
Ueno, Atsushi [1 ]
Tatsumi, Shoji [1 ]
机构：
[1] Osaka City Univ, Dept Phys Elect & Informat, Grad Sch Engn, Osaka 558, Japan
来源：
2008 CONFERENCE ON HUMAN SYSTEM INTERACTIONS, VOLS 1 AND 2 | 2008年
关键词：
Humanoid robot; game strategy; morphology; game piece recognition; game arrangement recognition;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We present a new approach for online learning an x-o game strategy by humanoid robot "hoap-3"*. No preset data for game playing are provided in advance. The proposed system mechanism simulates human decision making to carry out the online game learning. "haop-3" autonomously gains experience needed for learning the game strategy from the human partner. The more intelligent human partner, the faster humanoid robot "hoap-3" learning.
引用
收藏
页码：446 / 451
页数：6
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