Application of Deep Reinforcement Learning to NS-SHAFT Game Signal Control

Application of Deep Reinforcement Learning to NS-SHAFT Game Signal Control

Reinforcement learning (RL) with both exploration and exploit abilities is applied to games to demonstrate that it can surpass human performance. This paper mainly applies Deep Q-Network (DQN), which combines reinforcement learning and deep learning to the real-time action response of NS-SHAFT game...

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Bibliographic Details
Main Authors: Ching-Lung Chang, Shuo-Tsung Chen, Po-Yu Lin, Chuan-Yu Chang
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Sensors
Subjects:
reinforcement learning (RL)
game
real-time
Deep Q-Network (DQN)
deep learning
NS-SHAFT
Online Access:https://www.mdpi.com/1424-8220/22/14/5265

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https://www.mdpi.com/1424-8220/22/14/5265

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