DeepThought : The computer chess Champion
By : Anonymous Rebel
The artificial intelligence pioneer, Herbert Simon, predict-
ed that by 1967 a computer would be able to beat any human in
chess. However, he was quite far off. In 1989, the human mind
can still defeat even the greatest of computer chess machines.
Simon wasn't as far off as the critics of the Fifties, who
claimed that a computer could never master chess. A computer
called Deep Thought now plays at the level of a human grandmas-
ter, which means that only about 200 people in the world can
defeat him.
Deep Thought has not exactly been ranked as a grandmaster as
of yet, because according to Thomas Anantharaman, one of the
creators of Deep Thought, "You can't claim to be a grandmaster
unless you are a human being." However, this hasn't upset his
fellow creators or him. So far, they have won $10,000 from The
Fredkin Fund, for winning 25 straight games in world competition.
($100,000 is waiting for the first electronic world champion.)
Deep Thought follows the tradition of its computer predeces-
sors, by considering every possible move. Good human players
usually examine only a few moves, and rely on pattern recognition
and experience to succeed. This type of evaluation proves ex-
tremely difficult to program into a computer, although the former
computer chess champion, Hitech, was designed to recognized
certain programs. However, ruling out certain moves, without
fully examining all the possibilities will eventually lead to an
error in the computer's part.
Although a computer lacks the ability of insight, they make
it up in their ability to number crunch. For example, in a
typical situation, a chess player has 38 moves to consider. To
check all the responses would mean examining 1444 different
positions. To look one step ahead would mean checking over 2
million positions.
The secret of the computer's success, obviously, is its
incredible speed. Even a little toy chess computer is fast
enough to beat most people. The big time computers like Deep
Thought is even faster. In fact, the ultrafast electronics are
the source of power for all Fredkin prize hopefuls. Deep Thought
is simply the fastest around.
Deep thought is designed to examine five moves ahead. Since
this is far from seeing the end of a game, the machine must not
only check what positions it could end up in, but must evaluate
them as well. Typical considerations include the value of what
pieces will be captured, and whether the King will be put in
check. Deep Thought also checks its position on the board, and
the number of empty squares from which the King could be at-
tacked, and some 80 other items. Deep Thought gives numerical
values to all of the considerations, and uses the highest ranked
move.
All of the world-class chess computers uses certain varia-
tions on this approach. The reason for Deep Thought's success
is that it doesn't always hold itself to a few moves. If one
move seems particularly good, it searches down that path for up
to 15 moves. This strategy is called singular extension. If
Deep Thought registers an equally dangerous threat, it also
searches further, it works in the same manner, but this time its
called Threat Extension. If this feature comes into play, the
results are usually deadly for the opponent.
Deep Thought didn't used an experienced chess player to
assign relative values to its 80 considerations, like other chess
computers. Hitech had used Hans Berliner, a computer scientist
and a former world-class champion. "The fascination," Ananthara-
man says, "was writing a program that can do something I can't
do." Instead, the computer watched games played between human
grandmasters. One of the programmers "tuned" Deep Thought's
evaluation equation until it started choosing Grandmaster style
moves. First approximations were made in deciding the order.
Deep thought would use this hierarchy and replay the grandmaster
games. At first, Deep Thought played horribly. But after each
game, the program would change the rank slightly until Deep
Thought was playing like a true grandmaster. After 800 games,
Deep Thought was playing like a true master.
Anantharaman was truly surprised that the "tuning" worked as
well as it did. After evaluating the process, he decided that
this process is a better technique even if you have the expert
knowledge. The approach could also be used in other fields where
human experts aren't available. The trouble is that not many
problems are as well defined as that of chess. Some day the
thinking process would be useful to the military, but that is far
off. "Computer chess will give you an idea how to approach a
problem," says Anantharaman, "but it won't solve the problem
completely. I can't think of a single real-world problem that
has been solved by artificial intelligence."
Bibliography
"Pawn to King Four." Tom Waters. Discover Magazine,
May 1989. Volume 10, Number 5
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