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Quantitative Go, and some other combinatorial games
Colloquium| Speaker: | Elwyn Berlekamp, UC Berkeley |
| Location: | 693 Kerr |
| Start time: | Mon, Oct 14 2002, 4:10PM |
Description
Combinatorial game theory is concerned with two-person perfect-information
games, especially those classes of positions for which winning strategies
can be stated explicitly, or at least proved to exist. The powerful
mathematical methods (often requiring only paper and pencil, no computers)
are most successful when applied to games whose positions often decompose
into "sums". The many examples of such games include Nim, Dots and Boxes,
Hackenbush (best played with colored chalk and erasures), Domineering
(played with dominoes on a checkerboard), Konane (popular in ancient Hawaii),
Amazons (invented less than fifteen years ago, but which has attracted a
substantial following on the Internet), and Go (a popular Asian board
game dating back several thousand years, and which supports nearly
2,000 active professionals today). The theory also applies very well
to the fascinating new game called "Clobber", invented in Nova Scotia in
the summer of 2001.
In many of these games, a mathematically defined "temperature" provides a
numerical measure of the value of the next move. The extension of this
notion to loopy positions, such as kos in Go, appeared in "Games of No
Chance" in 1996. A subsequent extension, called "Environmental Go", includes
a stack of coupons in addition to the Go board. This has led to fruitful
collaborations between game theoreticians and professional 9-dan Go players.
For the past four years, we have been developing methods and techniques which
allow us to get rigorous analyses of the last 50 to 100 moves of some
professional games, and we not infrequently discover fatal mistakes.
We will present a broad introductory overview of this subject, including a
fascinating problem in which Go, chess, checkers, and domineering are
all played concurrently.
The time may now be ripe for new efforts to combine modern mathematical
game theory with alpha-beta pruning and other traditional AI minimax search
techniques.
