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Consider a two-dimensional convolution layer with 3x3 kernels. The 2d inputs of this layer can be seen as a particular graph with each pixel being a graph node, that is connected to 8 of his neighbors: The 3x3 kernels of the convolutional layer not only process the information about neighborhood relation between pixels, but also about their relative ...


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Bootstrapped estimate is biased because it based on $V(s_{t+1})$ which is usually a biased estimate by some estimator such as neural network. I don't think this statement is totally correct in the context of the paper. Quoting the paper: Taking $\gamma < 1$ introduces bias into the policy gradient estimate, regardless of the value function’s accuracy. ...


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