DocumentCode :
2337342
Title :
A game playing robot that can learn from experience
Author :
Abd El-Azim, R.A. ; Ueno, Atsushi ; Tatsumi, Shoji
Author_Institution :
Dept. of Phys. Electron. & Inf., Osaka City Univ., Osaka
fYear :
2008
fDate :
25-27 May 2008
Firstpage :
440
Lastpage :
445
Abstract :
We present a new approach for online learning an x-o game strategy by humanoid robot ldquohoap-3rdquo*. 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. ldquohaop-3rdquo autonomously gains experience needed for learning the game strategy from the human partner. The more intelligent human partner, the faster humanoid robot ldquohoap-3rdquo learning.
Keywords :
decision making; games of skill; humanoid robots; learning (artificial intelligence); mobile robots; experience-based learning; hoap-3 humanoid robot; human decision making; online game learning; online game playing robot; x-o game strategy; Actuators; Artificial intelligence; Decision making; Game theory; Humanoid robots; Humans; Informatics; Intelligent robots; Learning; Speech; Humanoid robot; game arrangement recognition; game piece recognition; game strategy; morphology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Human System Interactions, 2008 Conference on
Conference_Location :
Krakow
Print_ISBN :
978-1-4244-1542-7
Electronic_ISBN :
978-1-4244-1543-4
Type :
conf
DOI :
10.1109/HSI.2008.4581479
Filename :
4581479
Link To Document :
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