Can you explain the complexity of iterative deepening search?

Can you explain the complexity of iterative deepening search?

Sure! Iterative deepening search (IDS) combines the benefits of depth-first and breadth-first search. It explores the search space in a depth-first manner but does so iteratively, increasing the depth limit with each iteration.

What is the time complexity of IDS?

The time complexity of IDS is O(b^d), where b is the branching factor and d is the depth of the solution. This is similar to breadth-first search.

And what about the space complexity?

The space complexity of IDS is O(b*d), which is much more efficient than breadth-first search, making it suitable for deep search spaces.

Are there any drawbacks to using IDS?

Yes, while IDS is efficient in terms of space, it can be slower than other methods due to repeated exploration of nodes at shallower depths.

In what scenarios is IDS preferred?

IDS is preferred in scenarios where the search space is large and the depth of the solution is unknown, such as in puzzle solving or AI planning.