How can a computer play chess? For many people, that is a
mind-boggling concept. Chess seems like a distinctly human
activity, requiring intelligence and thought, so how can a
computer possibly do it?
In this edition of HowStuffWorks,
we will take a look at this question. What you will find is
that computers don't really "play" chess like people do. A
computer that is playing chess is not "thinking." Instead, it
is calculating through a set of formulas that cause it to make
good moves. As computers have gotten faster and faster, the
quality of these calculated moves has gotten better and
better. Computer chess calculators are now the best chess
players on the planet, even though they do it totally blindly.
People and Chess
have ever watched a person first learning to play chess, you
know that a human chess player starts with very limited
abilities. Once a player understands the basic rules that
control each piece, he or she can "play" chess. However, the
new player is not very good. Each early defeat comes as
something of a surprise -- "Oh, I didn't think about that!" or
"I didn't see that coming!" are common exclamations.
The human mind absorbs these experiences, stores away
different board configurations, discovers certain tricks and
ploys, and generally soaks up the nuances of the game one move
at a time. As the level of skill develops, the player will
often read books to discover patterns of play used by the best
players. Strategies and tactics develop to guide the player
through each game.
For a human being, therefore, the game of chess involves a
great deal of high-level abstract thought -- visual
pattern matching to recall board positions, rules and
guidelines, conscious thought and even psychology.
Computers do none of this...
Computers and Chess
state-of-the-art in computer chess is fairly intricate, but
all of it involves blind computation that is very simple at
Let's say you start with a chess board set up for the start
of a game. Each player has 16 pieces. Let's say that white
starts. White has 20 possible moves:
The white player chooses one of those 20 moves
and makes it.
- The white player can move any pawn forward one or two
- The white player can move either knight in two different
For the black player, the options are the same: 20 possible
moves. So black chooses a move.
Now white can move again. This next move depends on the
first move that white chose to make, but there are about 20 or
so moves white can make given the current board position, and
then black has 20 or so moves it can make, and so on.
This is how a computer looks at chess. It thinks about it
in a world of "all possible moves," and it makes a big
tree for all of those moves, like this:
In this tree, there are 20 possible moves for white. There
are 20 * 20 = 400 possible moves for black, depending on what
white does. Then there are 400 * 20 = 8,000 for white. Then
there are 8,000 * 20 = 160,000 for black, and so on. If you
were to fully develop the entire tree for all possible chess
moves, the total number of board positions is about
or 10120, give or take
a few. That's a very big number. For example, there have only
been 1026 nanoseconds since
Bang. There are thought to be only 1075 atoms in the
entire universe. When you consider that the Milky Way galaxy
contains billions of suns, and there are billions of galaxies,
you can see that that's a whole lot of atoms. That number is
dwarfed by the number of possible chess moves. Chess is a
pretty intricate game!
No computer is ever going to calculate the entire tree.
What a chess computer tries to do is generate the
board-position tree five or 10 or 20 moves into the future.
Assuming that there are about 20 possible moves for any board
position, a five-level tree contains 3,200,000 board
positions. A 10-level tree contains about 10,000,000,000,000
(10 trillion) positions. The depth of the tree that a computer
can calculate is controlled by the speed of the computer
playing the game. The fastest chess computers can generate and
evaluate millions of board positions per second.
Once it generates the tree, then the computer needs to
"evaluate the board positions." That is, the computer has to
look at the pieces on the board and decide whether that
arrangement of pieces is "good" or "bad." The way it does this
is by using an evaluation function. The simplest
possible function might just count the number of pieces each
side has. If the computer is playing white and a certain board
position has 11 white pieces and nine black pieces, the
simplest evaluation function might be:
Obviously, for chess that formula
is way too simple, because some pieces are more
valuable than others. So the formula might apply a weight to
each type of piece. As the programmer thinks about it, he or
she makes the evaluation function more and more complicated by
adding things like board position, control of the center,
vulnerability of the king to check, vulnerability of the
opponent's queen, and tons of other parameters. No matter how
complicated the function gets, however, it is condensed down
to a single number that represents the "goodness" of that
Three-Level Tree Diagram
diagram shows a three-level tree that looks three moves ahead
and has evaluated the value of the final board positions:
The computer is playing as the white player. The black
player has moved and left the board position at the top of the
tree. In this tree, white can make three possible moves. From
each of those three possible moves, black can make three
possible moves. From each of those nine board positions, white
can make two possible moves. (In real life, the total number
of moves from any position is 20 or so, but that would be hard
To decide what to do, the computer looks at this tree and
works upward from the bottom. Its calculations are set up so
that it finds the best board positions from each of the
possible positions black will take (it takes the maximum):
One level up, it assumes that black will choose the worst
possible position for white (it takes the minimum):
Finally, it takes the maximum of the top three numbers: 7.
That is the move the computer will make. Once black makes its
move, the computer goes through this whole process again,
generating a new tree and evaluating all of the board
positions to figure out its next move.
This approach is called the minimax algorithm
because it alternates between the maximums and minimums as it
moves up the tree. By applying a technique called alpha
beta pruning, the algorithm
can run about twice as fast and requires a lot less memory.
As you can see, this process is completely mechanical and
involves no thought. It is simply a brute force calculation
that applies an evaluation function to all possible board
positions in a tree of a certain depth.
What is interesting is that this sort of technique works
pretty well. On a fast-enough computer, the algorithm can look
far enough ahead to play a very good game. If you add in
learning techniques that modify the evaluation function based
on past games, the machine can even improve over time.
The key thing to keep in mind, however, is that this is
nothing like human thought. When we learn how human thinking
works and create a computer that uses those techniques to play
chess, we will really be onto something...
For more information on chess computers and related topics,
check out the links on the next page.
Lots More Information!
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