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The expected shape for the Keras DQNAgent model is a 2D convolutional neural network or a fully connected neural network. It can have one or multiple hidden layers depending on the complexity of the task being solved. The input shape of the model should match the input shape of the environment state. The output shape of the model should match the action space of the environment.