DocumentCode
2053481
Title
Fuzzy interpolation-based Q-learning with profit sharing plan scheme
Author
Horiuchi, Tadashi ; Fujino, Akinori ; Katai, Osamu ; Sawaragi, Tetsuo
Author_Institution
Dept. of Precision Eng., Kyoto Univ., Japan
Volume
3
fYear
1997
fDate
1-5 Jul 1997
Firstpage
1707
Abstract
We have previously (1996) proposed fuzzy interpolation-based Q-learning where fuzzy rules are used to represent Q-function (action utility function), in order to enable us to treat continuous-valued states and actions. In this paper, we will introduce the idea of profit sharing plan (PSP) used in classifier systems into the fuzzy interpolation-based Q-learning in order to accelerate the speed of learning and will discuss its effectiveness through applications to control problems such as cart-pole balancing problems
Keywords
fuzzy logic; interpolation; learning (artificial intelligence); action utility function; cart-pole balancing problems; classifier systems; continuous-valued actions; continuous-valued states; fuzzy interpolation-based Q-learning; profit sharing plan scheme; Acceleration; Autonomous agents; Control systems; Dynamic programming; Fuzzy control; Fuzzy systems; Inference algorithms; Learning; Neural networks; Precision engineering;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on
Conference_Location
Barcelona
Print_ISBN
0-7803-3796-4
Type
conf
DOI
10.1109/FUZZY.1997.619797
Filename
619797
Link To Document