Human Comprehensible Machine Learning

Contents

• Applying Programming by Demonstration in an Intelligent Authoring Tool for Cognitive Tutors

  Noboru Matsuda, William W. Cohen, and Kenneth R. Koedinger

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• Real-Time Interactive Reinforcement Learning for Robots

  Andrea Lockerd Thomaz, Guy Hoffman, and Cynthia Breazeal

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• Predicting User Tasks: I Know What You’re Doing!

  Simone Stumpf, Xinlong Bao, Anton Dragunov, Thomas G. Dietterich, Jon Herlocker, Kevin Johnsrude, Lida Li, and JianQiang Shen

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• TRIPPER: Rule Learning Using Taxonomies

  Flavian Vasile, Adrian Silvescu, Dae-Ki Kang, and Vasant Honavar

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• Comprehensibility of Generative vs. Class Discriminative Dynamic Bayesian Multinets

  John Burge, Terran Lane

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• Organizing Committee

  Dan Oblinger

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