Torrey, Lisa
Model AI Assignments 2016
Neller, Todd W. (Gettysburg College) | Brown, Laura E. (Michigan Technological University) | Marshall, James B. (Sarah Lawrence College) | Torrey, Lisa (St. Lawrence University) | Derbinsky, Nate (Wentworth Institute of Technology) | Ward, Andrew A. (Software Developer) | Allen, Thomas E. (University of Kentucky) | Goldsmith, Judy (University of Kentucky) | Muluneh, Nahom (University of Kentucky)
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 six AI assignments from the 2016 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs.
Crowd Simulation Via Multi-Agent Reinforcement Learning
Torrey, Lisa (St. Lawrence University)
Artificial intelligence is frequently used to control virtual characters in movies and games. When these characters appear in crowds, controlling them is called crowd simulation. In this paper, I suggest that crowd simulation could be accomplished by multi-agent reinforcement learning, a method by which groups of agents can learn to act autonomously in their environment. I present a case study that explores the challenges and benefits of this type of approach and encourages the development of learning techniques for AI in entertainment media.