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[Colloquium] Neural Network Architectures in Agent Based Simulations

November 30, 2012

Watch Colloquium: 

M4V file (681 MB)

  • Date: Friday, November 30, 2012 
  • Time: 12:00 pm — 12:50 pm 
  • Place: Centennial Engineering Center 1041

Thomas P. Caudell
Depts. of ECE, CS, and Psychology University of New Mexico 

Agent based simulation has proven itself as a valuable tool in the study of group dynamics. Agents range from particles to ants to robots to people to societies. Often, individual agent behavior is controlled by rule sets or statistical learning algorithms. In this talk, I will describe an aspect of our research that embeds biologically motivated artificial neural network architectures into agents that are endowed with a rich set of sensors and actuators. These agents reside in a 2D virtual Flatland where we are able conduct experiments that measure their performance as a function of neural architecture. I will begin with an introduction to neural networks, describe the simulated agents and Flatland, and then work through a series of architectures from simple to complex, describing their operation and the effects they have on agent behavior. I will end with a discussion of future directions in this type of research.


Bio: Thomas P. Caudell was appointed to direct UNM’s Center for High Performance Computing beginning in February 2007. Promoted to full professor in 2007, Dr. Caudell’s research interests include neural networks, virtual reality, machine vision, robotics and genetic algorithms. He teaches courses in programming, computer games, neural networks, virtual reality, computer graphics and pattern recognition. He has been active in the field of virtual reality and neural networks since 1986, has more than 75 publications in these areas, and in 1993 helped organize IEEE.s first Virtual Reality Annual International Symposium. He is also an active member of the IEEE, the International Neural Network Society, and the Association for Computing Machinery.