NDLI: Reinforcement learning of fuzzy logic controllers for quadruped walking robots

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Reinforcement learning of fuzzy logic controllers for quadruped walking robots

Content Provider	Semantic Scholar
Author	Gu, Dongbing Hu, Huosheng
Copyright Year	2002
Abstract	This paper presents a fuzzy logic controller (FLC) for the implementation of some behaviour of Sony legged robots. The adaptive heuristic Critic (AHC) reinforcement learning is employed to refine the FLC. The actor part of AHC is a conventional FLC in which the parameters of input membership functions are learned by an immediate internal reinforcement signal. This internal reinforcement signal comes from a prediction of the evaluation value of a policy and the external reinforcement signal. The evaluation value of a policy is learned by temporal difference (TD) learning in the critic part that is also represented by a FLC. A genetic algorithm (GA) is employed for learning internal reinforcement of the actor part because it is more efficient in searching than other trial and error search approaches. Copyright © 2002 IFAC
Starting Page	825
Ending Page	825
Page Count	1
File Format	PDF HTM / HTML
DOI	10.3182/20020721-6-ES-1901.00827
Volume Number	15
Alternate Webpage(s)	http://cswww.essex.ac.uk/staff/hhu/Papers/IFAC2002.pdf
Alternate Webpage(s)	https://www.researchgate.net/profile/Huosheng_Hu/publication/2880695_Reinforcement_Learning_of_Fuzzy_Logic_Controllers_for_Quadruped_Walking_Robots/links/02bfe50e9654dd7402000000.pdf
Alternate Webpage(s)	http://folk.ntnu.no/skoge/prost/proceedings/ifac2002/data/content/03045/3045.pdf
Alternate Webpage(s)	https://doi.org/10.3182/20020721-6-ES-1901.00827
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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