

Depth-First Iterative Deepening (1985) [pdf] - brudgers
http://www.cse.sc.edu/~mgv/csce580f09/gradPres/korf_IDAStar_1985.pdf

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austinl
I recently implemented depth-first iterative deepening in an Artificial
Intelligence class project to solve the classic missionaries and cannibals
problem [0]. The professor remarked that while there have been some
optimizations over the last few decades, using them can be quite messy – to
the point where the combination of A* and iterative deepening is still
commonly used in the field.

I'm fairly certain that the claim in the introduction – "Unfortunately,
current AI texts either fail to mention this algorithm or refer to it only in
the context of two-person game searches" – is no longer true.

From my current textbook (Artificial Intelligence: A Modern Approach [1]):

"Iterative deepening search (or iterative deepening depth-first search) is a
general strategy, often used in combination with depth-first tree search, that
finds the best depth limit. It does this by gradually increasing the limit —
first 0, then 1, then 2, and so on — until a goal is found... In general,
iterative deepening is the preferred uninformed search method when the search
space is large and the depth of the solution is not known."

[0]
[http://en.wikipedia.org/wiki/Missionaries_and_cannibals_prob...](http://en.wikipedia.org/wiki/Missionaries_and_cannibals_problem)

[1] [http://www.amazon.com/Artificial-Intelligence-Modern-
Approac...](http://www.amazon.com/Artificial-Intelligence-Modern-Approach-
Edition/dp/0136042597)

