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...
Main Authors: | Levent Akin, Toygar Karadeniz |
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Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2008-11-01
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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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