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cs.LG2019
Learning a Behavioral Repertoire from Demonstrations
Niels Justesen, Miguel Gonzalez Duque, Daniel Cabarcas Jaramillo +2
Imitation Learning (IL) is a machine learning approach to learn a policy from a dataset of demonstrations. IL can be useful to kick-start learning before applying reinforcement lea…
cs.NE2019
Deep Neuroevolution of Recurrent and Discrete World Models
Sebastian Risi, Kenneth O. Stanley
Neural architectures inspired by our own human cognitive system, such as the recently introduced world models, have been shown to outperform traditional deep reinforcement learning…