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Songs can be well arranged by professional music curators to form a riveting playlist that creates engaging listening experiences. However, it is time-consuming for curators to timely rearrange these playlists for fitting trends in future. By exploiting the techniques of deep learning and reinforcement learning, in this paper, we consider music playlist generation as a language modeling problem and solve it by the proposed attention language model with policy gradient. We develop a systematicdoi:10.5281/zenodo.1492370 fatcat:w3fajmvqpbalrc62ubwi3djnge