Using games and simulation to teach AI

Document Type

Conference Proceeding

Place of Publication

Perth, Western Australia


School of Computer and Information Science


Hingston, P. & Coombes, B. (2005). Using games and simulation to teach AI. Paper presented at The Reflective Practitioner, Proceedings of Annual Teaching and Learning Forum, Curtin University of Technology, Perth, Western Australia. https://litec.curtin.edu.au/events/conferences/tlf/tlf2005/refereed/hingston.html


There is an important and enduring relationship between artificial intelligence (AI) and games. Historically, games such as chess, backgammon, checkers, poker and, more recently, Go,have provided pivotal challenge problems for AI researchers, exposing and elucidating the nature of intelligence. It seems especially fitting, then, to use games to teach students about aspects of intelligence and how it may be artificially simulated.

Contemporary students seem less interested in traditional board and card games, and more interested in real time interactive strategy games such as Starcraft, massively multiplayer online role playing games such as The Saga of Ryzom, or first person shooters such as Unreal Tournament or Counterstrike. These games also use AI techniques to provide intelligent computer players, known as NPCs (non-player characters) or "bots" (short for robots) as opponents for human players. This presents an opportunity for AI educators to motivate students to learn about AI technologies by designing learning experiences around the use of AI in these kinds of games, while also introducing them to an important application area.

Interactive learning can exploit the facilities provided by technology to cater for diverse learning styles and individual differences. These learning experiences support constructivist learning pedagogy where students build on prior and acquired knowledge to develop deeper meaning and understandings (About Learning, 2004). Learning materials that use constructivist principles have the capacity to engage students in open ended, inquiry based learning that encourages interaction with the learning materials as a major part of the learning process. Individual learning and motivational styles, such as those identified in the 4MAT System: Imaginative Learning; Analytic Learning; Common Sense Learning and Dynamic Learning (McCarthy, 2004), can also be built into online learning materials through the use of alternative pathways and activities (Combes & Ring, 2004). These considerations underpin the development of an AI programming toolkit that provides illustrative animated displays, and the creation of programming assignments where students use the toolkit to develop intelligent bots for a simple real time animated battle game with simulated physics.

The rest of this paper is structured as follows. The first section briefly reviews the historical relationship between AI and games. The next section focuses on previously reported educational use of games for teaching AI, and relevant educational theory on learning styles and pedagogy. This is followed by a description of the simulated battle scenario and the task that was set for the students, as well as the main features of the AI toolkit. The final section presents a report of the students' response to the task and the learning experience.