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de Bruin, T.D. (author), Kober, J. (author), Tuyls, Karl (author), Babuska, R. (author)Deep reinforcement learning makes it possible to train control policies that map high-dimensional observations to actions. These methods typically use gradient-based optimization techniques to enable relatively efficient learning, but are notoriously sensitive to hyperparameter choices and do not have good convergence properties. Gradient...journal article 2020
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de Bruin, T.D. (author), Verbert, K.A.J. (author), Babuska, R. (author)Timely detection and identification of faults in railway track circuits are crucial for the safety and availability of railway networks. In this paper, the use of the long-short-term memory (LSTM) recurrent neural network is proposed to accomplish these tasks based on the commonly available measurement signals. By considering the signals from...journal article 2017