How do iterative deepening search and breadth-first search compare?

How do iterative deepening search and breadth-first search compare?

Iterative deepening search (IDS) combines the benefits of depth-first search 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. This allows it to find the shortest path like breadth-first search while using less memory.

What are the advantages of using iterative deepening search?

The main advantages of iterative deepening search are its low memory usage, as it only needs to store a single path from the root to a leaf node, and its ability to find the optimal solution in an unweighted graph, similar to breadth-first search.

Are there any disadvantages to iterative deepening search?

Yes, one disadvantage is that it can be slower than breadth-first search because it repeatedly explores the same nodes in each iteration, leading to redundant work.

In what scenarios would you prefer breadth-first search over iterative deepening search?

Breadth-first search is preferable when the search space is shallow and memory is not a constraint, as it guarantees the shortest path and explores all nodes at the present depth before moving deeper.