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Incorporating Tutorial Strategies Into an Intelligent Assistant
Jim R. Davies, Neal Lesh, Charles Rich, Candace L. Sidner, Abigail S. Gertner,
Jeff Rickel
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Organizations Involved
• College of Computing, Georgia Institute of Technology (Davies)
• Mitsubishi Electric Research Labs (Lesh, Rich, Sidner)
• The MITRE Corporation (Gertner)• USC Information Sciences Institute
(Rickel)
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Motivating Example
• Long camping trip
• Someone tutors you on how to set up a tent
• As time passes, that tutor becomes an assistant
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Research Goal
• To show that assisting and tutoring are two points on the same spectrum by building an agent that can transition between both behaviors.
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Intellectual History
• Collaborative Assisting Agent (COLLAGEN)– assists with software applications
• COLLAGEN generated interest in learning to use applications.
• We are extending COLLAGEN so it can tutor and built an agent called Triton.
http://www.cc.gatech.edu/~jimmyd/research/triton/
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COLLAGEN (COLLaborative Agent)
• Middleware
• Discourse theory of collaboration
• Shared plan theory• Rich, C. and Sidner, C. L. (1998). COLLAGEN: A
collaboration manager for software interface agents. User Modeling and User-Adapted Interaction, Vol. 8, No. 3/4, 315—350.
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Assistant Scenario
• User: Let’s plan the second leg of the trip.
• Assistant: Okay.
• User: [selects Washington] What next?
• Assistant: [points to San Francisco] I will select San Francisco.
• User: Okay.
• Assistant: [selects San Francisco]
• User: What next?
• Assistant: Let’s remove an airline constraint.
http://www.cc.gatech.edu/~jimmyd/research/triton/
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ITS Background
• Domains: physics and algebra
• Domain Knowledge
• Student Model
• Pedagogical knowledge• Wenger, E. (1987). Artificial Intelligence and
Tutoring Systems. Morgan Kaufmann Publishers, Inc. Los Altos, CA.
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Tutoring Scenario (part 1)
• User: What next?
• Triton: Please specify the route of the trip.
• User: What next?
• Triton: Select Atlanta and then select Boston.
• User: What next?
• Triton: Please select Atlanta.
• User: What next?
• Triton: [points to Atlanta with cursor] Please click on the dot near Atlanta on the map.
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Tutoring Scenario (cont.)
• User: [clicks on Atlanta] What next?
• Triton: Please select Boston.
• User: [clicks on Dallas]
• Triton: Oops! What you did was select Dallas; what you should have done was select Boston. I will bring you back to the previous state by clicking undo. [undo] Please select Boston.
• User: [clicks on Boston]
• Triton: Great job!
• User: What next?
• Triton: Select the dates and times of travel.
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Goal of this research
• Add to COLLAGEN to give it tutoring behaviors
• Adjustable parameters
• Triton
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Worked Examples
• Worked examples are kinds of recipes
http://www.cc.gatech.edu/~jimmyd/research/triton/
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The User is Not Always Right
• Determining when a task is completed
• Responding to Errors
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Responding to Errors
• Intervene after n unrecognizable actions
• What the intervention looks like:– Say what the student did– Say what the student should have done– Undo to get to previous state
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Tutors are not Maximally Helpful
• Because of learning goals
• Waiting for Student Initiative
• Suggesting actions without doing them
• Explaining
• Demonstrating
• Pointing
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Learning Goals
• Usually task goals are in service of learning goals, but not always
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Waiting For Student Initiative
• In assisting, always try to help
• In tutoring, get student to try herself
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Suggesting Actions Without Doing Them
• Should you force the user to do all actions?
• Agent suggests doing, but doesn’t do.
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Explaining (cont.)
• Composite Actions– list of task descriptions
• Primitive Actions– application-level description of what to do
on screen
• Stored as explanation recipes
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Demonstrating
• Behavior:– Do a sequence of actions– Undo them
• Stored as explanation recipes
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Pointing
• In assisting, point when proposing
• In tutoring, point when explaining a primitive
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Summary of Parameters
• When to intervene after error detection
• Who defaults to do actions
• When to point
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Contributions
• Middleware
• Use of recipes as a single representational structure for:– abstract actions– utterances– explanations– demonstrations
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Conclusions
• This work bridges the gap between tutoring and assisting
• Smoothly transitions between them
• Based on collaborative discourse theory
http://www.cc.gatech.edu/~jimmyd/research/triton/
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Future Work
• Student Model
• Automatic Shifting between assisting and tutoring