DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-10,Issue-10 ( Oct, 2023 ) | |||||||||
Paper Title |
DQN-VIZ: A Deep Q-Network Visualization System | |||||||||
Author Name |
Mohsin Wani, Mudasir Mohd., Hilal Ahmad Khanday | |||||||||
Affilition |
Sr. Assistant Professor, Department of Computer Science, University of Kashmir | |||||||||
Pages |
37-39 | |||||||||
Abstract |
DQN and its variations are one of the primary deep reinforcement learning algorithms used for discrete action spaces. Applying these algorithms to a particular task can be difficult and considering the number of parts involved, debugging such implementations require lot of time and effort. Our objective here is to develop a library that in addition to providing implementations of several popular variations of DQN algorithms gives access to a support system that can aid in analyzing, recording and debugging whilst applying deep reinforcement learning to the problem at hand. Keywords - Deep Reinforcement Learning, DQN, Double DQN, Dueling DQN, Recording | |||||||||
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