Authors:
Marc Pouly
;
Thomas Koller
and
Ruedi Arnold
Affiliation:
School of Information Technology, Lucerne University of Applied Sciences and Arts and Switzerland
Keyword(s):
Teaching Artificial Intelligence, Card Game Playing Platform, Open Source Software, Student Competition, Contextualized Education.
Related
Ontology
Subjects/Areas/Topics:
Active Learning
;
Computer-Supported Education
;
e-Learning
;
Game-Based and Simulation-Based Learning
;
Learning/Teaching Methodologies and Assessment
;
Pattern Recognition
;
Theory and Methods
Abstract:
Man vs. machine competitions have always been attracting much public attention and the famous defeats of human champions in chess, Jeopardy!, Go or poker undoubtedly mark important milestones in the history of artificial intelligence. In this article we reflect on our experiences with a game-centric approach to teaching artificial intelligence that follows the historical development of algorithms by popping the hood of these champion bots. Moreover, we made available a server infrastructure for playing card games in perfect information and imperfect information playing mode, where students can evaluate their implementations of increasingly sophisticated game-playing algorithms in weekly online competitions, i.e. from rule-based systems to exhaustive and heuristic search in game trees to deep learning enhanced Monte Carlo methods and reinforcement learning completely freed of human domain knowledge. The evaluation of this particular course setting revealed enthusiastic feedback not on
ly from students but also from the university authority. What started as an experiment became part of the standard computer science curriculum after just one implementation.
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