# Tag Info

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Welcome to AI.SE @Kate_Catelena! I teach AI courses at the undergraduate level, and so have seen a lot of semester projects over the years. Here are some templates that often lead to exciting outcomes: Pick a new board or card game, and write a program to play it. Your course has probably covered Adversarial Search, and may also have covered Monte Carlo ...

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Here are some possible options Music Generation using GA/MA Open AI's gym projects 2048 on RL and search algorithms Fixing bugs in the source code of some AI software project

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Given that the neurons are linear in the hidden layer of the neural network, so the output is just the dot product of the weights and the input. To put things in perspective, generally, we use an activation function (sigmoid, signum, etc.), which is applied to the dot product. Hence, for an input of $3$ inputs to node 1 of hidden layer is $-3 * 3 = -9$, to ...

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The loss function (aka cost function) measures the correctness of the predictions of the model. For example, a simple cost function could be $|y - f(x)|$, where $\hat{y} = f(x)$ is the prediction of the model $f$ when the input is $x$, $y$ is the ground-truth label for input $x$ (i.e. what the model is supposed to output when the input is $x$), and \$|\...

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This question really looks like a homework problem, in part because it is too vague (what does it mean to 'get stuck' exactly?). Hill climbing stops when it reaches a local maximum. Hill climbing is an uninformed search algorithm, so it does not make use of a heuristic. Hill climbing may or may not stop on a ridge, depending on the implementation. Some ...

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Initial state: initial position of the monkey. Possible actions climb on the crate, get down the crate, move the crate from one spot to another, stack one crate on another, walk from one spot to another, grab bananas (if standing on the crate) Goal test: did the monkey get the bananas? Cost function: the number of actions completed

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