Dr. Peter Stone is an Alfred P. Sloan Research Fellow, Guggenheim
Fellow, AAAI Fellow, Fulbright Scholar, and Professor in the
Department of Computer Science at the University of Texas at Austin.
He received his Ph.D. in 1998 and his M.S. in 1995 from Carnegie
Mellon University, both in Computer Science.  He received his B.S. in
Mathematics from the University of Chicago in 1993.  From 1999 to 2002
he was a Senior Technical Staff Member in the Artificial Intelligence
Principles Research Department at AT&T Labs - Research.

Prof. Stone's research interests include planning, machine learning,
multiagent systems, robotics, and e-commerce.  Application domains
include robot soccer, autonomous bidding agents, traffic management,
and autonomic computing. His doctoral thesis research contributed a
flexible multiagent team structure and multiagent machine learning
techniques for teams operating in real-time noisy environments in the
presence of both teammates and adversaries. He has developed teams of
robot soccer agents that have won seven robot soccer tournaments
(RoboCup) in both simulation and with real robots.  He has also
developed agents that have won five auction trading agent competitions
(TAC).  Prof. Stone is the author of "Layered Learning in Multiagent
Systems: A Winning Approach to Robotic Soccer" (MIT Press, 2000) as
well as a co-author of "Autonomous Bidding Agents: Strategies and
Lessons from the Trading Agent Competition" (MIT Press, 2007).  In
2003, he won a CAREER award from the National Science Foundation for
his research on learning agents in dynamic, collaborative, and
adversarial multiagent environments.  In 2004, he was named an ONR
Young Investigator for his research on machine learning on physical
robots.  In 2007, he was awarded the prestigious IJCAI Computers and
Thought award, given once every two years to the top AI researcher
under the age of 35.  In 2013 he was awarded the University of Texas
System Regents' Outstanding Teaching Award.