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: Levent Akin, Toygar Karadeniz
Format: Article
Language:English
Published: SAGE Publishing 2008-11-01
Series:International Journal of Advanced Robotic Systems
Subjects:
Online Access:http://www.intechopen.com/articles/show/title/fdms_with_q-learning__a_neuro-fuzzy_approach_to_partially_observable_markov_decision_problems

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