We outline the applications of deep reinforcement learning in NLP, including dialog (Li et al., 2016) , semi-supervised text classification (Wu et al., 2018) , coreference (Clark and Manning, 2016; Yin et al., 2018) , knowledge graph reasoning<cite> (Xiong et al., 2017</cite> ), text games (Narasimhan et al., 2015; He et al., 2016a) , social media (He et al., 2016b; Zhou and Wang, 2018) , information extraction (Narasimhan et al., 2016; Qin et al., 2018) , language and vision (Pasunuru and Bansal, 2017; Misra et al., 2017; Wang et al., 2018a,b,c; Xiong et al., 2018) , etc.