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p.27 Throughout this book we will be discussing representations. The reason
for this is that in order for a computer to solve a problem that relates to the real world, it first
needs some way to represent the real world internally. In dealing with that internal representation, the computer
is then able to solve problems.
p.28-29 As we will see elsewhere in the book, the representation that is used to represent a problem is
very important. In other words, the way in which the computer represents a problem, the variables it uses, and the
operators it applies to those variables can make the difference between an efficient algorithm and an algorithm that doesn't
work at all. This is true of all Artificial Intelligence problems, and as we see in the following chapters, it is
vital for search...The more difficult problem is to determine the data structure that will be used to represent the problem
we are exploring... When applying Artificial Intelligence to search problems, a useful, efficient, and meaningful
representation is essential. In other words, the representation should be such that the computer does not waste too
much time on pointless computations, it should be such that the representation really does relate to the problem that is being
solved, and it should provide a means by which the computer can actually solve the problem.
p.146 Evaluation functions (also known as static evaluators because they
are used to evaluate a game from just one static position) are vital to most game-playing computer programs. This is because
it is almost never possible to search the game tree fully due to its size. Hence, a search will rarely reach a leaf
node in the tree at which the game is either won, lost, or drawn, which means that the software needs to be able
to cut off search and evaluate the position of the board at that node. Hence, an evaluation function is used to examine a
particular position of the board and estimate how well the computer is doing, or how likely it is to win from this position.
Due to the enormous number of positions that must be evaluated in game playing, the evaluation function usually needs
to be extremely efficient, to avoid slowing down game play.
p.469 The blackboard architecture is a method for structured knowledge
representation that was invented in the 1970s by H. Penny Nii (Nii 1986) for a system called HEARSAY-II...The idea
behind blackboard systems is that disparate knowledge from different expert sources can be combined by providing a central
database - the blackboard - on which the experts (known as knowledge sources) can "write" information. Because the blackboard
is shared, one knowledge source can see facts appear as another knowledge source puts them there, and it can thus deduce new
facts and add them to the blackboard. In this way, a number of knowledge sources can be used together to solve a complex problem,
but each knowledge expert does not need to know from where the data on the blackboard came.
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