Model AI Assignments

  • Todd Neller
  • , John DeNero
  • , Dan Klein
  • , Sven Koenig
  • , William Yeoh
  • , Xiaoming Zheng
  • , Kenny Daniel
  • , Alex Nash
  • , Zachary Dodds
  • , Giuseppe Carenini
  • , David Poole
  • , Chris Brooks

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

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. Assignment specifications and supporting resources may be found at http://modelai. gettysburg.edu.

Original languageEnglish
Title of host publicationAAAI-10 / IAAI-10 - Proceedings of the 24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference
PublisherAI Access Foundation
Pages1919-1921
Number of pages3
ISBN (Print)9781577354666
StatePublished - 2010
Event24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference, AAAI-10 / IAAI-10 - Atlanta, GA, United States
Duration: Jul 11 2010Jul 15 2010

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume3

Conference

Conference24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference, AAAI-10 / IAAI-10
Country/TerritoryUnited States
CityAtlanta, GA
Period07/11/1007/15/10

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