[talks] FW: Michael Littman, Rutgers, TODAY, 4:25 PM

[Ginny Hogan]

The Princeton-Yahoo! machine learning speaker series continues TODAY with
Michael Littman from Rutgers University.

Michael is the director of the Rutgers Laboratory for Real-Life
Reinforcement Learning (RL^3) and his research in machine learning examines
algorithms for decision making under uncertainty.

Michael will be giving a talk TODAY, at 4:25pm, in CS 105 (small
auditorium).  The title and abstract for his talk are included below and can
also be found on the website for the Princeton-Yahoo! speaker series:
http://ai.cs.princeton.edu/pmwiki/pmwiki.php?n=Public.Talks.

---

Efficiently Learning to Behave Efficiently Michael Littman Rutgers
University

The field of reinforcement learning is concerned with the problem of
learning efficient behavior from experience. In real life applications,
gathering this experience is time-consuming and possibly costly, so it is
critical to derive algorithms that can learn effective behavior with bounds
on the experience necessary to do so. This talk presents our successful
efforts to create such algorithms within a novel learning-theory framework
we call "KWIK" for "knows what it knows". I'll summarize the framework, our
algorithms, their formal validations, and their empirical evaluations in
robotic and videogame testbeds.