Are DFS and BFS complete?

Are DFS and BFS complete?

Answer: BFS is complete and optimal, while DFS is not guaranteed to halt when there are loops. Answer: If m is the maximum path length and b is the branching factor, the space complexity for DFS is mb while for BFS it is bm.

What do you mean by completeness of a search Why DFS is not always complete?

Completeness: DFS is complete if the search tree is finite, meaning for a given finite search tree, DFS will come up with a solution if it exists. Optimality: DFS is not optimal, meaning the number of steps in reaching the solution, or the cost spent in reaching it is high.

How do you know when to use DFS over BFS?

15 Answers

1. If you know a solution is not far from the root of the tree, a breadth first search (BFS) might be better.
2. If the tree is very deep and solutions are rare, depth first search (DFS) might take an extremely long time, but BFS could be faster.

Is breadth first search Complete?

Breadth-first search is complete, but depth-first search is not. When applied to infinite graphs represented implicitly, breadth-first search will eventually find the goal state, but depth first search may get lost in parts of the graph that have no goal state and never return.

Why is the BFS complete and the DFS not?

How is then that the BFS is complete and the DFS is not, since the completeness of the BFS relies on the branching factor being finite! A tree can be infinite without having an infinite branching factor. As an example, consider the state tree for Rubik’s Cube.

Can DFS get stuck in a cycle?

Still, as you point out, in a finite tree, DFS will eventually find the solution if it exists. DFS can not stuck in cycles (if we have a list of opened and closed states). The algorithm is not complete since it does not find a solution in an infinite space, even though the solution is in depth d which is much lower than infinity.

When is DFS optimal?

However, DFS is optimal when the search tree is finite, all action costs are identical and all solutions have the same length. However limitating this may sound, there is an important class of problems that satisfies these conditions: the CSPs (constraint satisfaction problems).

What is the difference between depth first search and BFS?

If the tree is very deep and solutions are rare, depth first search (DFS) might take an extremely long time, but BFS could be faster. If the tree is very wide, a BFS might need too much memory, so it might be completely impractical.