2023/6/30 -Deep Q-Network (DQN) is a groundbreaking algorithm that combines deep neural networks with Q-learning for reinforcement learning tasks. Its ability to learn ...
2023/9/26 -The DQN (Deep Q-Network) algorithm was developed by DeepMind in 2015. It was able to solve a wide range of Atari games (some to superhuman level) by ...
2023/8/7 -In this section, we present a novel distributed hybrid algorithm that considers the strength of both model predictive control and deep reinforcement learning.
2024/3/23 -Deep Q-Network (DQN) is a groundbreaking algorithm that combines the principles of reinforcement learning with the power of deep neural networks.
2024/3/18 -Essentially, deep Q-Learning replaces the regular Q-table with the neural network. Rather than mapping a (state, action) pair to a Q-value, the neural network ...
90K views · 34:05. Go to channel · Deep Q-Learning/Deep Q-Network (DQN) Explained | Python Pytorch Deep Reinforcement Learning. Johnny Code•12K views · 9:15. Go ...
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2023/12/22 -At the heart of a DQN Agent is a QNetwork , a neural network model that can learn to predict QValues (expected returns) for all actions, given an observation ...
2023/6/14 -Deep Q-Network (DQN) combines deep neural networks with Q-learning algorithm to approximate the optimal state or action-value function of an agent in a given ...
2023/7/8 -This study is focused on the prediction of financial distress in companies in addition to the wider application of Deep Q-Network in multiclass classification.
2023/10/5 -The Deep Q-Network is a deep reinforcement learning algorithm that extends Q-learning to handle high-dimensional state spaces. It employs a neural network to ...