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Summary: PLOW: A Collaborative Task Learning Agent
James Allen, Nathanael Chambers
, George Ferguson
, Lucian Galescu, Hyuckchul Jung, Mary
Swift
, William Taysom
Institute for Human and Machine Cognition, 40 S Alcaniz St, Pensacola, FL
Dept. of Computer Science, Stanford University, Stanford, CA
Dept. of Computer Science, University of Rochester, Rochester, NY
jallen@ihmc.us
Abstract
To be effective, an agent that collaborates with humans
needs to be able to learn new tasks from humans they work
with. This paper describes a system that learns executable
task models from a single collaborative learning session
consisting of demonstration, explanation and dialogue. To
accomplish this, the system integrates a range of AI tech-
nologies: deep natural language understanding, knowledge
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