DocumentCode
1685356
Title
A pulse neural network learning algorithm for POMDP environment
Author
Takita, Koichiro ; Hagiwara, Masafumi
Author_Institution
Fac. of Sci. & Technol., Keio Univ., Yokohama, Japan
Volume
2
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
1643
Lastpage
1648
Abstract
In this paper, we propose a new pulse neural network model and its reinforcement learning algorithm. The main purpose of this model is to utilize pulse neurons´ ability to handle sequential inputs in partially observable Markov decision process (POMDP). Its performance is confirmed by computer simulation
Keywords
Markov processes; decision theory; learning (artificial intelligence); neural nets; POMDP environment; computer simulation; partially observable Markov decision process; pulse neural network learning algorithm; reinforcement learning algorithm; Artificial intelligence; Artificial neural networks; Biological system modeling; Biology computing; Computer networks; Computer simulation; History; Learning; Neural networks; Neurons;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location
Honolulu, HI
ISSN
1098-7576
Print_ISBN
0-7803-7278-6
Type
conf
DOI
10.1109/IJCNN.2002.1007764
Filename
1007764
Link To Document