Q Learning Regression Neural Network
Q Learning Regression Neural Network
- New search for: Sarıgül, Mehmet
- New search for: Avcı, Mutlu
- New search for: Sarıgül, Mehmet
- New search for: Avcı, Mutlu
- New search for: orcid:0000-0001-7323-6864
- New search for: Sarıgül, Mehmet
WOS: 000449440400001 ; In this work, a Nadaraya-Watson kernel based learning system which owns general regression neural network topology is adapted to Q learning method to evaluate a quick and efficient action selection policy for reinforcement learning problems. By means of the proposed method Q value function is generalized and learning speed of Q agent is accelerated. The training data of the developed neural network are obtained by a standard Q learning agent on closed-loop simulation system. The efficiency of the proposed method is tested on popular reinforcement learning benchmarks and its performance is compared with other popular regression methods and Q-learning utilized methods. QLRNN increased the learning performance and it learns faster than other methods on selected benchmarks. Test results showed the efficiency and the importance of the proposed network.
Document information
Q Learning Regression Neural Network
2018-01-01
431
Article (Journal)
Electronic Resource
English
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