T. Neller, S. Keeley, M. Guerzhoy, W. Hoenig, J. Li, S. Koenig, A. Soni, K. Thomason, L. Zhang, B. Sebatian, C. Resnick, A. Oliver, S. Bhupatiraju, K. Agrawal, J. Allingham, S. Yoon, J. Chen, T. Larsen, M. Neumann, N. Norouzi, R. Hausen and M. Evett. Model AI Assignments 2020. In Proceedings of the Symposium on Educational Advances in Artificial Intelligence (EAAI), pages 13509-13511, 2020.

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 nine AI assignments from the 2020 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.

Our Model AI Assignment on 'Multi-Agent Path Finding' is available here.

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This page was automatically created by a bibliography maintenance system that was developed as part of an undergraduate research project, advised by Sven Koenig.