DocumentCode :
2628275
Title :
Emotionally motivated reinforcement learning based controller
Author :
Ayesh, Aladdin
Author_Institution :
De Montfort Univ., Leicester
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
874
Abstract :
There have been several attempts to model emotions in autonomous agents and robotics. The use of emotions in conjunction with reinforcement learning in particular has attracted attention since both notions are borrowed analogies from psychology. The work presented here is an approach to robot control based on modeling emotions within reinforcement learning algorithm. The main contribution of this paper is the use of fuzzy cognitive maps (FCM) to facilitate the modeling of emotions and inferencing for action selection. This approach does not use feeling estimation; instead a direct link between sensory data and emotions is used for emotional estimation. An emotion based reinforcement learning algorithm is proposed for action selection in robotic control
Keywords :
cognitive systems; fuzzy set theory; learning (artificial intelligence); robots; emotional estimation; emotionally motivated reinforcement learning; fuzzy cognitive maps; robot control; Cognitive robotics; Computational intelligence; Fuzzy cognitive maps; Fuzzy logic; Inference algorithms; Learning; Neural networks; Psychology; Robot control; Robot sensing systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2004 IEEE International Conference on
Conference_Location :
The Hague
ISSN :
1062-922X
Print_ISBN :
0-7803-8566-7
Type :
conf
DOI :
10.1109/ICSMC.2004.1398413
Filename :
1398413
Link To Document :
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