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: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2004-12-01
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| Series: | International Journal of Advanced Robotic Systems |
| Online Access: | https://doi.org/10.5772/5817 |
| _version_ | 1818316512245579776 |
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| author | Toygar Karadeniz Levent Akin |
| author_facet | Toygar Karadeniz Levent Akin |
| author_sort | Toygar Karadeniz |
| collection | DOAJ |
| description | 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 decision making and Q-learning. |
| first_indexed | 2024-12-13T09:22:36Z |
| format | Article |
| id | doaj.art-7b743a4080354a5a9de2e92045f1a7a1 |
| institution | Directory Open Access Journal |
| issn | 1729-8814 |
| language | English |
| last_indexed | 2024-12-13T09:22:36Z |
| publishDate | 2004-12-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | International Journal of Advanced Robotic Systems |
| spelling | doaj.art-7b743a4080354a5a9de2e92045f1a7a12022-12-21T23:52:41ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142004-12-01110.5772/581710.5772_5817FDMS with Q-Learning: A Neuro-Fuzzy Approach to Partially Observable Markov Decision ProblemsToygar KaradenizLevent AkinFinding 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 decision making and Q-learning.https://doi.org/10.5772/5817 |
| spellingShingle | Toygar Karadeniz Levent Akin FDMS with Q-Learning: A Neuro-Fuzzy Approach to Partially Observable Markov Decision Problems International Journal of Advanced Robotic Systems |
| title | FDMS with Q-Learning: A Neuro-Fuzzy Approach to Partially Observable Markov Decision Problems |
| title_full | FDMS with Q-Learning: A Neuro-Fuzzy Approach to Partially Observable Markov Decision Problems |
| title_fullStr | FDMS with Q-Learning: A Neuro-Fuzzy Approach to Partially Observable Markov Decision Problems |
| title_full_unstemmed | FDMS with Q-Learning: A Neuro-Fuzzy Approach to Partially Observable Markov Decision Problems |
| title_short | FDMS with Q-Learning: A Neuro-Fuzzy Approach to Partially Observable Markov Decision Problems |
| title_sort | fdms with q learning a neuro fuzzy approach to partially observable markov decision problems |
| url | https://doi.org/10.5772/5817 |
| work_keys_str_mv | AT toygarkaradeniz fdmswithqlearninganeurofuzzyapproachtopartiallyobservablemarkovdecisionproblems AT leventakin fdmswithqlearninganeurofuzzyapproachtopartiallyobservablemarkovdecisionproblems |