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Deep Q-Networks: machine learning on steroids
Deep Q-Networks (DQN) are an advanced method of machine learning based on the combination of deep neural networks and Q-learning. They are designed to solve complex sequential decision problems where an agent acts in an environment and learns to perform optimal actions. DQNs use a deep neural network to approximate the Q-function, which represents the expected future utility of an action in a given state. Through iterative training, it learns [...]
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