To this end, we borrow ideas from imitation learning for structured prediction (Daume et al., 2009;Ross et al., 2011;Goldberg and Nivre, 2013;.
we cast agenda-based semantic parsing as a Markov decision process, where the goal is to learn a policy, that given a state (i.e., the current chart and agenda), chooses the best next action (i.e., the parse to pop from the agenda).