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The Learned Value of Control model introduces a method of approximating the expected value of control by associating individual stimulus features with control values. This project consisted of implementing two different learning mechanisms for the LVOC model, one that uses Bayesian linear regression and one that uses a neural network.

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The Learned Value of Control model introduces a method of approximating the expected value of control by associating individual stimulus features with control values. This project consisted of implementing two different learning mechanisms for the LVOC model, one that uses Bayesian linear regression and one that uses a neural network.

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