Interactive Task Learning for Robotics and Embodied Dialogue Agents


Motivations and Objectives

We envision that the forthcoming generation of artificial intelligence (AI) will adopt an embodied paradigm: one that enables AI agents to operate in the physical world, interpret and process multimodal inputs, learn from situated communication with humans, and collaborate with humans on complex tasks. The potential impact of embodied AI is tremendous, spanning from robots that serve as waiters in restaurants and assist elderly individuals to complete household chores, to the aspiration of artificial general intelligence.

Our thoughts and positions:

Selected Recent Papers

Embodied Dialogue Agents for Instruction Following

Interactive Task Learning from Situated Dialogue