Hill Climbing - Artificial Intelligence:

As we've seen, in some problems, finding the search path from primary to goal state is the point of the exercise. In other problems, the path and the artefact at the end of the path are both important, and we regularly try to find optimal solutions. Just for a certain set of problems, the path is irrelevant and finding appropriate artefact is the sole purpose of the search. In such cases, it doesn't be matter whether our agent searches down a path for 10 or 1000 steps, as long as it may be finds a solution in the end.

For example, consider the 8-queens problem in which we decided where the task is to find an sequence of 8 queens on a chess board such that no one can "take" another (one queen can take another if it's on the same horizontal, vertical or diagonal line. A Solution for this type of problem is:

One possible way to justify this problem is with states where there are a number of queens (1 to 8) on the board, and an action is to add a queen in this like a way that it can't take another. Its tottaly depending on your strategy, you may find that the search needs much more back-tracking, i.e., towards the end, and you find that you simply can't put the last queens on anywhere, so that you have to move one of the queens you put down earlier (you go back-up the search tree).