[Intelligence Seminar] May 13, 2014 12:00 noon: Presentation by Michael Bowling

[Jill Lentz]

INTELLIGENCE SEMINAR
MAY 13 AT 12:00 NOON, IN NSH 1507
(UNUSUAL TIME)

SPEAKER: MICHAEL BOWLING (University of Alberta)
Host: Ariel Procaccia
For meetings, contact Pat Loring (sawako at cs.cmu.edu<mailto:sawako at cs.cmu.edu>)

ADVERSARIES, ABSTRACTIONS, AND ALGORITHMS

The Computer Poker Research Group at the University of Alberta has for
over a decade developed the strongest poker playing programs in the
world. We have tested them in competition against other programs, winning
20 of 33 events since the inauguration of the AAAI Computer Poker
Competition in 2006. We have also tested them against top professional
players, becoming the first to beat professional poker players in a
meaningful competition in 2008. Our success follows the modus operandi of
the very pioneers of game theory: when facing an intractably complex game,
abstract the game to a smaller one and reason in that game. "It seems to
us...," as Von Neumann and Morgenstern wrote, "its decisive properties
will be conserved in our simplified form." Recently, this approach has
been shown to be on shaky ground, or rather on no ground at all. In this
talk, I will be looking down to see what, if anything, the abstraction
methodology can stand on; and what this line of research means for
real-world applications where abstraction is step one, as well as
applications that do not involve an apparent adversary.

BIO

Michael Bowling is a Professor of Computing Science at the University of
Alberta. His research focuses on artificial intelligence, machine
learning, and game theory; and he is particularly fascinated by the
problem of how computers can learn to play games through experience.
Michael is the leader of the Computer Poker Research Group, which has
built some of the strongest poker playing programs in the world. In 2008,
one of these programs, Polaris, defeated a team of top professional poker
players in two-player, limit Texas Hold'em, becoming the first program to
defeat poker pros in a meaningful competition. He also pioneered the
Arcade Learning Environment, a testbed for developing artificial
intelligence that can exhibit general competence across a variety of
domains. His research has been featured on the television programs
Scientific American Frontier and National Geographic Today; in print
articles in the New York Times and Wired; and twice in exhibits at the
Smithsonian Museums in Washington, D.C.


Jill M. Lentz
Language Technologies Institute
School of Computer Science
Carnegie Mellon University
6509 Gates Hillman Complex
5000 Forbes Avenue
Pittsburgh, PA 15213
jlentz at cs.cmu.edu<mailto:jlentz at cs.cmu.edu>

T:  (412)268-1593
F:  (412)268-6298


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