FDMS with Q-Learning: A Neuro-Fuzzy Approach to Partially Observable Markov Decision Problems

Finding optimal solutions to Partially Observable Markov Decision Problems is known to be NP-hard. This paper describes a novel neuro-fuzzy approach to obtain fast, robust and easily interpreted solutions by utilizing a combination of several learning techniques including neural networks, fuzzy deci...

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Bibliographic Details
Main Authors: Toygar Karadeniz, Levent Akin
Format: Article
Language:English
Published: SAGE Publishing 2004-12-01
Series:International Journal of Advanced Robotic Systems
Online Access:https://doi.org/10.5772/5817