Paper: Demonstration of PLOW: A Dialogue System for One-Shot Task Learning

ACL ID N07-4001
Title Demonstration of PLOW: A Dialogue System for One-Shot Task Learning
Venue Human Language Technologies
Session Main Conference
Year 2007
Authors

Various specialized reasoning modules in the system communicate and collaborate with each other to interpret the user’s intentions, build a task model based on the interpretation, and check consistency between the learned task and prior knowledge. The play-by-play approach in NL enables our task learning system to build a task with highlevel constructs that are not inferable from observed actions alone. In addition to the knowledge about task structure, NL also provides critical information to transform the observed actions into more robust and reliable executable forms. Our system learns how to find objects used in the task, unifying the linguistic information of the objects with the semantic representations of the user’s NL descriptions about them. The objects can then be reliably fo...