Researchers'
robot playing poker
Theory could be
applied to e-commerce
Network World staff
Computer scientists have moved
beyond figuring out how to beat
computerised chess systems and are
now tackling
automated Texas Hold'Em
programs.
Carnegie Mellon University
researchers have created a robot
that uses knowledge of game theory
to beat online Texas Hold'Em
programs.
The GS1 poker robot, which makes
decisions after analysing poker
rules, was created by Tuomas
Sandholm, director of Carnegie
Mellon's Agent-Mediated
Electronic Marketplaces Lab and
graduate student Andrew Gilpin.
Sandholm says the challenge of
developing a poker robot is greater
than that of trying to beat a
computerised chess program because,
unlike chess, poker involves making
decisions with incomplete
information. You know what pieces an
opposing chess player has, but don't
know the hand of a competing poker
player.
An algorithm used to accommodate
such uncertainties to play poker
might have applications in
e-commerce, such as in auctions,
says Sandholm, who has done
significant amounts of research on
e-commerce. He is chairman and chief
scientist of CombineNet, a company
that helps large organisations save
money and time on procurement.
The latest version of Sandholm's
poker robot, dubbed GS2, will
partake in the Computer Poker
Competition during the National
Conference on Artificial
Intelligence 16-20 July in Boston