From the Lab to the Classroom and Beyond: Extending a Game-Based Research Platform for Teaching AI to Diverse Audiences

Recent years have seen increasing interest in AI from outside the AI community. This is partly due to applications based on AI that have been used in real-world domains, for example, the successful deployment of game theory-based decision aids in security domains. This paper describes our teaching approach for introducing the AI concepts underlying security games to diverse audiences. We adapted a game-based research platform that served as a testbed for recent research advances in computational game theory into a set of interactive role-playing games. We guided learners in playing these games as part of our teaching strategy, which also included didactic instruction and interactive exercises on broader AI topics. We describe our experience in applying this teaching approach to diverse audiences, including students of an urban public high school, university undergraduates, and security domain experts who protect wildlife. We evaluate our approach based on results from the games and participant surveys.

[1]  Sarit Kraus,et al.  Deployed ARMOR protection: the application of a game theoretic model for security at the Los Angeles International Airport , 2008, AAMAS 2008.

[2]  Milind Tambe,et al.  Robust Protection of Fisheries with COmPASS , 2014, AAAI.

[3]  Elizabeth Sklar,et al.  Teaching AI using LEGO Mindstorms , 2004 .

[4]  Milind Tambe,et al.  "A Game of Thrones": When Human Behavior Models Compete in Repeated Stackelberg Security Games , 2015, AAMAS.

[5]  Rong Yang,et al.  Adaptive resource allocation for wildlife protection against illegal poachers , 2014, AAMAS.

[6]  Bo An,et al.  PROTECT: a deployed game theoretic system to protect the ports of the United States , 2012, AAMAS.

[7]  Juliane Hahn,et al.  Security And Game Theory Algorithms Deployed Systems Lessons Learned , 2016 .

[8]  Leon Sterling,et al.  Teaching AI algorithms using animations reinforced by interactive exercises , 1997, ACSE '97.

[9]  Milind Tambe,et al.  Patrol Strategies to Maximize Pristine Forest Area , 2012, AAAI.

[10]  Vincent Conitzer,et al.  Stackelberg vs. Nash in security games: interchangeability, equivalence, and uniqueness , 2010, AAMAS.

[11]  Sven Koenig,et al.  Teaching Artificial Intelligence and Robotics Via Games , 2010, EAAI.

[12]  John DeNero,et al.  Teaching Introductory Artificial Intelligence with Pac-Man , 2010, Proceedings of the AAAI Conference on Artificial Intelligence.

[13]  Milind Tambe,et al.  Using Science Fiction in Teaching Artificial Intelligence , 2008, AAAI Spring Symposium: Using AI to Motivate Greater Participation in Computer Science.

[14]  Milind Tambe,et al.  When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing , 2015, IJCAI.

[15]  Michael Wollowski Teaching With Watson , 2014, AAAI.