Task-Oriented Language Grounding for Language Input with Multiple Sub-Goals of Non-Linear Order

27 Oct 2019 Vladislav Kurenkov Bulat Maksudov Adil Khan

In this work, we analyze the performance of general deep reinforcement learning algorithms for a task-oriented language grounding problem, where language input contains multiple sub-goals and their order of execution is non-linear. We generate a simple instructional language for the GridWorld environment, that is built around three language elements (order connectors) defining the order of execution: one linear - "comma" and two non-linear - "but first", "but before"... (read more)

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