DocumentCode :
2006772
Title :
Application of Manifold Learning methods to scene information in video games
Author :
Handa, Hiroyuki
Author_Institution :
Sch. of Sci. & Eng., Kindai Univ., Higashi-Osaka, Japan
fYear :
2012
fDate :
20-24 Nov. 2012
Firstpage :
290
Lastpage :
295
Abstract :
We have shown that the Isomap, one of the most famous Manifold Learning method, is suitable for Neu-roevolution of mobile robots with redundant inputs. In the proposed method, a large number of high dimensional inputs are collected in advance. The Manifold Learning method yields the low dimensional space. Evolutionary Learning is carried out with the low dimensional inputs, instead of the original high dimensional inputs. In this paper, the Isomap and Manifold Sculpting are compared by using Mario AI Championship.
Keywords :
computer games; evolutionary computation; learning (artificial intelligence); mobile robots; Isomap; Mario AI championship; evolutionary learning; low dimensional space; manifold learning methods; manifold sculpting; mobile robots; neuroevolution; redundant inputs; scene information; video games;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on
Conference_Location :
Kobe
Print_ISBN :
978-1-4673-2742-8
Type :
conf
DOI :
10.1109/SCIS-ISIS.2012.6505281
Filename :
6505281
Link To Document :
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