Browsing by Subject "College of Science and Engeineering"

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    Deep QWOP Learning
    (2017) Wu, Hung-Wei;
    We apply a deep learning model to the QWOP flash game, which requires control of a ragdoll athlete using only the keys “Q”, “W”, “O”, and “P”. The model is a convolutional neural network trained with Q-learning. By training the model with only raw pixel input, we show that our model is capable of successfully learning a control policy associated with playing QWOP. This model was successfully applied to a non-deterministic control environment in the form of a ragdoll physics flash game.