Model AI Assignments

Authors

  • Todd Neller Gettysburg College
  • John DeNero University of California, Berkeley
  • Dan Klein University of California, Berkeley
  • Sven Koenig University of Southern California
  • William Yeoh University of Southern California
  • Xiaoming Zheng University of Southern California
  • Kenny Daniel University of Southern California
  • Alex Nash University of Southern California
  • Zachary Dodds Harvey Mudd College
  • Giuseppe Carenini University of British Columbia
  • David Poole University of British Columbia
  • Chris Brooks University of San Francisco

DOI:

https://doi.org/10.1609/aaai.v24i3.18837

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 eight AI assignments that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs.

 

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Published

2010-07-15

How to Cite

Neller, T., DeNero, J., Klein, D., Koenig, S., Yeoh, W., Zheng, X., Daniel, K., Nash, A., Dodds, Z., Carenini, G., Poole, D., & Brooks, C. (2010). Model AI Assignments. Proceedings of the AAAI Conference on Artificial Intelligence, 24(3), 1919-1921. https://doi.org/10.1609/aaai.v24i3.18837

Issue

Vol. 24 No. 3 (2010): First Symposium on Education Advances in Artificial Intelligence

Section

EAAI Symposium Model AI Assignments