Murray Campbell on how he became interested in computers:
"Well, interestingly enough, [I became interested in
computers] when I was in high school, in Edmonton, Canada, I went to the
University of Alberta for an open-house...and at that point I saw a computer
playing chess.
"I was a chess player at the time and that fascinated me. I ended up going
into the Computer Science Department there and getting my degree, then going
on to get my Ph.D. in Computer Science at Carnegie Mellon. So you could say
that got me started."
Murray Campbell is the only member of the Deep Blue development team who can
say that his interest in chess led him to pursue a career in computer
science. Campbell grew up in Edmonton, Alberta, Canada, becoming a strong
expert-level player while still in high school. After seeing the computer
chess demonstration at the University of Alberta, he was hooked. The rest, as
they say, is history.
@ Carnegie Mellon
Campbell received his bachelor's and master's degrees in Computing Science
from the University of Alberta in 1981. He specialized in parallel search in
the context of chess, a discipline that served him well in developing
massively parallel computers like Deep Blue.
He left Canada to enroll at Carnegie Mellon University as a doctoral
candidate in Computer Science. Campbell received his Ph.D. in 1987 from CMU
for his work on chunking as an abstraction mechanism in solving complex
problems.
At Carnegie Mellon he met a fellow doctoral student named Feng-hsiung Hsu who
had developed a single-chip chess move generator. The two teamed up in the
autumn of 1986 to construct a chess-playing computer, Chiptest, that
eventually evolved into Deep Blue. Both Campbell and Hsu joined IBM in 1989.
Role on the Deep Blue team
Brody was recruited into the Deep Blue project in 1990. "Actually, I was
between projects, and they were bringing Murray Campbell and Feng-hsiung Hsu
[to IBM]. Hsu had worked on this machine, the Deep Thought machine, and they
said, 'How would you like to work on this project?' And I said, 'Why not?
Sounds great.' And we've been together ever since. It's a good team. We work
well together."
Campbell's role on the Deep Blue team is twofold. His main function is the
development of the evaluation function, or the component of Deep Blue that
assesses the value of the current position.
"That's very important," says Campbell, "because even if you can search many
moves into a position, search forward all the possible moves, it's still, you
have to evaluate those positions at the end of the sequence of moves that
you've looked at. If you evaluate them incorrectly, you're going to play poor
chess." Campbell's challenge is to help Deep Blue evaluate positions
accurately 100% of the time.
He also works closely with the team's chess consultant, international
grandmaster Joel Benjamin, in developing Deep Blue's opening book (link to
N.2)
This year's match
Campbell feels that this year's match will be even more competitive than last
year's battle. "We know that Deep Blue is going to be playing at a higher
level than last year," he says. "Deep Blue -- the current version of Deep
Blue -- has already beaten the last version in several test games that we've
played. So we know that it's better."
But Campbell isn't quite ready to predict a victory for Deep Blue. "We also
know that Kasparov has spent a lot of time, and is spending a lot of time,
preparing for this match and will come to this match with some new ideas on
how to play against computers, so that will be interesting."
Campbell was the recipient of an IBM Outstanding Innovation Award for his
work on the Deep Blue project. His interests include data-mining and
parallel-search algorithms.
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