Mapping Instructions and Visual Observations to Actions with Reinforcement Learning

EMNLP, pp. 1004-1015, 2017.

Cited by: 96|Views68
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Abstract:

We propose to directly map raw visual observations and text input to actions for instruction execution. While existing approaches assume access to structured environment representations or use a pipeline of separately trained models, we learn a single model to jointly reason about linguistic and visual input. We use reinforcement learning...More

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