How to optimally solve the flood fill puzzle?

As a heuristic, you could construct a graph where each node represents a set of contiguous, same-colour squares, and each node is connected to those it touches. (Each edge weighted as 1). You could then use a path-finding algorithm to calculate the “distance” from the top left to all other nodes. Then, by looking the … Read more

Prerequisites Needed to Read Books on Neural Networks (and understand them)

If you want a list of college courses that you’ll need to understand the book, here it is: Calculus (I, II and III) Differential Equations Linear Algebra Statistics (or a good covering of Bayes) However, I did just fine in my NN classes without Diff. Eq. and just had to look up concepts I hadn’t … Read more

How many possible states does the 8-puzzle have?

9! is the total number of possible configurations of the puzzle, whereas 9!/2 is the total number of solvable configurations. For example, this configuration doesn’t have a solution: 1 2 3 4 5 6 8 7 Read more about the solvability of certain configurations of the n-puzzle in this Wikipedia article, or as pointed out … Read more

How to choose number of hidden layers and nodes in neural network? [closed]

Note: this answer was correct at the time it was made, but has since become outdated. It is rare to have more than two hidden layers in a neural network. The number of layers will usually not be a parameter of your network you will worry much about. Although multi-layer neural networks with many layers … Read more

Continuous output in Neural Networks

Much of the work in the field of neuroevolution involves using neural networks with continuous inputs and outputs. There are several common approaches: One node per value Linear activation functions – as others have noted, you can use non-sigmoid activation functions on output nodes if you are concerned about the limited range of sigmoid functions. … Read more

Rush Hour – Solving the game

For classic Rush Hour, this problem is very tractable with a simple breadth first search. The claimed hardest known initial configuration requires 93 moves to solve, with a total of only 24132 reachable configurations. Even a naively implemented breadth-first search algorithm can explore the entire search space in under 1 second on even a modest … Read more

How to engineer features for machine learning [closed]

Good feature engineering involves two components. The first is an understanding the properties of the task you’re trying to solve and how they might interact with the strengths and limitations of the classifier you’re using. The second is experimental work where you will be testing your expectations and find out what actually works and what … Read more

Meaning of parameters in torch.nn.conv2d

Here is what you may find torch.nn.Conv2d(in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True, padding_mode=”zeros”) Parameters in_channels (int) – Number of channels in the input image out_channels (int) – Number of channels produced by the convolution kernel_size (int or tuple) – Size of the convolving kernel stride (int or tuple, optional) – Stride of the … Read more

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