Faster than Real-Time Machine Learning within High Fidelity Simulations

March 27, 2002
1:30 pm - 2:30 pm
Halligan 111
Speaker: Ethan Danahy
Host: Dr. S. Morrison


Imagine using a virtual learning environment to remove the programmer from the process of developing code for mechanical movement. Efficient artificial intelligence combined with a high fidelity simulation would allow the computer to discover valid, optimal actions for a robot in faster than real-time, thus eliminating the need for human guess-and-test. This presentation presents the challenges of developing such a system, and describes a robotic machine and associated simulation that gives testimony to this possibility.