In this paper we present a new method for improving reinforcement learning training times under the following two assumptions: (1) we know the conditions under which the environment gives reward; and (2) we can control the initial state of the environment at the beginning of a training episode. Our method, called intra-task curriculum learning, presents the different episode starting states to an agent in order of increasing distance to immediate reward.
CITATION STYLE
du Preez-Wilkinson, N., Gallagher, M., & Hu, X. (2018). Intra-task curriculum learning for faster reinforcement learning in video games. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11320 LNAI, pp. 65–70). Springer Verlag. https://doi.org/10.1007/978-3-030-03991-2_6
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