Robotic learning from multimodal instructions: a card game case study
Abstract: This chapter describes the design and evaluation of a learning agent capable of receiving multimodal instructions from a human teaching it how to play a card game. The system design includes a corpus-based grammar, a common representation for both input modalities that is used by the agent’s higher-level knowledge, and dialogue components. The initial deployment of the system was as a computer-based agent interacting with human instructors via speech and a touch screen. Our evaluation of this configuration consisted of two experiments involving human users who interacted with the agent using free-flowing speech and card moves executed ...
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