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arXiv · 2010.09890

Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration

Xavier Puig·Tianmin Shu·Shuang Li·Zilin Wang·Yuan-Hong Liao·Joshua B. Tenenbaum·Sanja Fidler·Antonio Torralba
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Abstract

In this paper, we introduce Watch-And-Help (WAH), a challenge for testing social intelligence in agents. In WAH, an AI agent needs to help a human-like agent perform a complex household task efficiently. To succeed, the AI agent needs to i) understand the underlying goal of the task by watching a single demonstration of the human-like agent performing the same task (social perception), and ii) coordinate with the human-like agent to solve the task in an unseen environment as fast as possible (human-AI collaboration). For this challenge, we build VirtualHome-Social, a multi-agent household environment, and provide a benchmark including both planning and learning based baselines. We evaluate the performance of AI agents with the human-like agent as well as with real humans using objective metrics and subjective user ratings. Experimental results demonstrate that the proposed challenge and virtual environment enable a systematic evaluation on the important aspects of machine social intelligence at scale.

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Xavier Puig, Tianmin Shu, Shuang Li, Zilin Wang, Yuan-Hong Liao, Joshua B. Tenenbaum, Sanja Fidler, Antonio Torralba. 2020-10-19. Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration. https://arxiv.org/abs/2010.09890

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