All the searches we discuss have their niche in the body of
problems we ask computer to solve-this is evidenced by their continued use
and continued efforts to optimize them. There is no "ideal" search
algorithm for every situation, or even a large number of situations. This,
in part, is because questions which are answered by search are far from homogenous
in nature. Two player games cannot be solved in the same way one would find
an ideal route for a map; and even among such categories, the same search
may not be as useful for one game (say, chess) as another (say, backgammon,
which includes chance) .
A more interesting optimization is that of the heuristic devices common to intelligent search. One search may be slightly more efficient than another in a certain scenario, but designing a better heuristic will always speed things up-and even make things possible that otherwise were not. What can we do with better heuristics? Everything from smarter traffic lights to smarter video games.
In a field as broad and complex as artificial intelligence, it is often hard to have a good place to establish foundation for a basic understanding. These searches, though at the core of the artificial intelligence's most advanced theories and most notable achievements, are nonetheless comprehensible to relatively inexperienced computer scientists. We hope that from this basic understanding, knowledge of the deepest parts of this vast area can begin to grow.