The concept of adversarial agent is related to recent studies on adversarial examples for image classifiers-it has been shown that a carefully designed small perturbation can easily make neural networks mis-classify (Goodfellow et al., 2014;Szegedy et al., 2013;Moosavi Dezfooli et al., 2016;Carlini and Wagner, 2017;Cheng et al., 2019), and several recent works has extended these attacks to natural language processing models such as sentiment analysis (Gao et al., 2018;Yang et al., 2018) and machine translation (Ebrahimi et al., 2018;.
all of the previous work consider attacking a static model, where except input im-age/sentence there is no interaction between the attacker and the target model.