A Survey on Dialog Management: Recent Advances and Challenges [article]

Yinpei Dai, Huihua Yu, Yixuan Jiang, Chengguang Tang, Yongbin Li, Jian Sun
2021 arXiv   pre-print
Dialog management (DM) is a crucial component in a task-oriented dialog system. Given the dialog history, DM predicts the dialog state and decides the next action that the dialog agent should take. Recently, dialog policy learning has been widely formulated as a Reinforcement Learning (RL) problem, and more works focus on the applicability of DM. In this paper, we survey recent advances and challenges within three critical topics for DM: (1) improving model scalability to facilitate dialog
more » ... m modeling in new scenarios, (2) dealing with the data scarcity problem for dialog policy learning, and (3) enhancing the training efficiency to achieve better task-completion performance . We believe that this survey can shed a light on future research in dialog management.
arXiv:2005.02233v3 fatcat:hc5o572kk5ciffiq27la6clm2y