The `QNetwork.forward` method in Python is a function that computes the forward pass of a Q-network model. A Q-network is a type of reinforcement learning model used to approximate the action-value function, which predicts the expected future rewards for different actions taken in a given state.
In the `forward` method, the input state is passed through the layers of the Q-network model, consisting of fully connected layers or convolutional layers. This process involves multiplying the input by weight matrices and applying activation functions to produce output values for each node in the network.
The output of the `forward` method is the estimated action-values, which represent the predicted rewards for each possible action in the given state. These action-values are then used to determine the best action to take in a reinforcement learning scenario, such as playing a game or controlling a robot.
Overall, the `QNetwork.forward` method plays a crucial role in training and utilizing Q-network models, as it calculates the predicted action-values based on the input state.
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