The FAIM Lab is concerned with a variety of problems in interactive media, including digital and non-digital games as well as apps and websites.
We borrow approaches from game studies, software verification, HCI, and AI to explore questions like:

  1. How can we formally model this game or app in such a way that a computer can make sense of it? How is it similar to or different from others like it, and what are its consituent parts?
  2. Given a model like this, what properties can we prove about the model? Is it possible to win the game within some time limit? Will all winning plays include a certain event? For an idealized player, what is the expected value of their score for a particular section of the game? Will someone who is color blind have difficulty with a particular interaction, or is a sound effect likely to be played in a repetitive and potentially annoying way?
  3. Could we use information like that to generate new game levels or complete games?
  4. How can we write a computer program that automatically learns a model like the one above—the rules and interaction structures—from observations of play or from playing by itself?
  5. If a computational system learns information about one game or app, how could we help it transfer that knowledge to other games or apps?

Each of these challenging problems is a starting point for a variety of research questions around a particular game or game genre, for example, and as we tackle a broader variety of interactive systems we can synthesize novel insights about the questions themselves: what their answers tell us about human perception, interaction, learning, and creativity.