Reading between the Lines: Learning to Map High-Level Instructions to Commands
S. R. K. Branavan, Luke Zettlemoyer, Regina Barzilay · DSpace@MIT (Massachusetts Institute of Technology) · 2010
In this paper, we address the task of mapping high-level instructions to se-quences of commands in an external en-vironment. Processing these instructions is challenging—they posit goals to be achieved without specifying the steps re-quired to complete them. We describe a method that fills in missing informa-tion using an automatically derived envi-ronment model that encodes states, tran-sitions, and commands that cause these transitions to happen. We present an ef-ficient approximate approach for learning this environment model as part of a policy-gradient reinforcement learning algorithm for text interpretation. This design enables learning for mapping high-level instruc-tions, which previous statistical methods cannot handle.1 1