Overview
Syllabus
Introduction
Explanationable AI
Shared Expectations
Classification and Interpretation
Task Execution
Demonstrations
Learning from demonstration
Learning from demonstration pipeline
Treebased demonstrations
Takeaways
Algorithm
Collaborative Robotics
Query Analysis
Key Takeaway
Using Robots to Shape Human Behavior
Learning from Environment
Compounding State Vector
Tracking Belief
Communication
Pseudocoup
Rules
Experiment
Hypothesis
Results
Sentimental Intelligence
Motivation
Issues
Summary
Feedback
Policy elicitation
Conclusion
Natural Language Understanding
Humanism
Not Talking
Out of Field
Statespace
Enable
Exaggeration
Machine Learning
Taught by
Paul G. Allen School