AAAI Publications, Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence

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Social State Recognition and Knowledge-Level Planning for Human-Robot Interaction in a Bartender Domain
Ronald P. A. Petrick, Mary Ellen Foster, Amy Isard

Last modified: 2012-07-15


We discuss preliminary work focusing on the problem of combining social interaction with task-based action in a dynamic, multiagent bartending domain, using an embodied robot. We show how the users' spoken input is interpreted, discuss how social states are inferred from the parsed speech together with low-level information from the vision system, and present a planning approach that models task, dialogue, and social actions in a simple bartending scenario. This approach allows us to build interesting plans, which have been evaluated in a real-world study, using a general purpose, off-the-shelf planner, as an alternative to more mainstream methods of interaction management.


Language Grounding; Natural Language Understanding; Reasoning about Plans; Planning with Incomplete Information; Knowledge Representation and Reasoning; Dialogue

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