DocumentCode :
3186674
Title :
Reinforcement learning in continuous state space with perceptual aliasing by using complex-valued RBF network
Author :
Shibuya, Takeshi ; Arita, Hideaki ; Hamagami, Tomoki
Author_Institution :
Grad. Sch. of Syst. & Inf. Eng., Univ. of Tsukuba, Tsukuba, Japan
fYear :
2010
fDate :
10-13 Oct. 2010
Firstpage :
1799
Lastpage :
1803
Abstract :
Reinforcement learning for continuous state space with perceptual aliasing is proposed. Complex-valued reinforcement learning is effective for perceptual aliasing. In continuous state space, the conventional complex-valued reinforcement learning demands the discretization of continuous state. However, it is difficult to discretize continuous state suitably. In this paper, complex-valued reinforcement learning using complex-valued RBF network is proposed. An experiment shows that proposed method is effective for continuous state space with perceptual aliasing.
Keywords :
Markov processes; antialiasing; learning (artificial intelligence); radial basis function networks; Markov process; complex valued RBF Network; continuous state space; perceptual aliasing; reinforcement learning; Radial basis function networks; complex-valued reinforcement learning; partially observable Markov decision Processes; perceptual Aliasing; reinforcement learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems Man and Cybernetics (SMC), 2010 IEEE International Conference on
Conference_Location :
Istanbul
ISSN :
1062-922X
Print_ISBN :
978-1-4244-6586-6
Type :
conf
DOI :
10.1109/ICSMC.2010.5642294
Filename :
5642294
Link To Document :
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