When eight-year-old Beth Harmon’s parents are killed in
an automobile accident, she’s placed in an orphanage in Mount
Sterling, Kentucky. Plain and shy, Beth learns to play chess
from the janitor in the basement and discovers she is a prodigy.
The thrilling novel of one young woman’s journey through the
worlds of chess and drug addiction.
BOOK COMPANION Editor Gerry Andeen Discusses The Queen's Gambit
This
is a story about finding out things as you grow up. We
begin with Beth Harmon in an orphanage. She is a bright
child and gets to clap the erasers in the basement where she
sees the janitor with his attention on a chess board. We
follow her through the things she learns and experiences,
friends, sex, addictions, etc. as she eventually plays the world
champion chess grandmaster master. One does not have to
know much about chess to enjoy the story, but increasing
knowledge enhances the reading experience. I think the
book should be required reading for students of Artificial
Intelligence as well as of child development, and maybe chess.
A common way to think about a chess move is to consider the
position and find a good move from that position. That is
the way the early artificial intelligence game playing programs
worked. They considered every possible move from a given
position, and every possible response, followed by the first
player’s second move, down to as many levels as you could afford
given machine speed and memory. Then the machine evaluated
all the end positions, picked the best one and made the move
that led to that position. Beside the large move tree
created, the problem was to devise that critical evaluation
algorithm.
What is clear from The Queen’s Gambit is that, in
addition to considering the board position, the master players
think in terms of groups of moves. They are often named
for players who played them in famous games, Sillian defense,
Queens gambit, Morphy’s branch. The chess road is well
trod and simply looking at a position does not take advantage of
the accumulated chess knowledge. Now I am not familiar
with what is going on in chess AI, especially how neural
networks are employed. If the neural networks are only
looking at a position, can they be improved by considering
patterns of play?
As already suggested, the book is more than about chess.
It is about discovery and learning. It is about people and
their interactions with each other.