2019
AAAI
AAAI 2019
Model AI Assignments 2019
Abstract
Abstract The Model AI Assignments session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community. Recognizing that assignments form the core of student learning experience, we here present abstracts of ten AI assignments from the 2019 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at http: //modelai.gettysburg.edu.
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Conference Pioneer
— AAAI 2019
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Keyword Pioneer
— assignment design
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics
Authors
Todd W. Neller
,
Raja Sooriamurthi
,
Michael Guerzhoy
,
Lisa Zhang
,
Paul Talaga
,
Christopher Archibald
,
Adam Summerville
,
Joseph Osborn
,
Cinjon Resnick
,
Avital Oliver
,
Surya Bhupatiraju
,
Kumar Krishna Agrawal
,
Nate Derbinsky
,
Elena Strange
,
Marion Neumann
,
Jonathan Chen
,
Zac Christensen
,
Michael Wollowski
,
Oscar Youngquist