What is breadth-first search in AI?

What is breadth-first search in AI?

Breadth-first search (BFS) is an algorithm for traversing or searching tree or graph data structures. It explores all neighbors at the present depth prior to moving on to nodes at the next depth level.

Can you explain how BFS works step by step?

Sure! BFS starts at a selected node and explores all its neighbors. It uses a queue to keep track of nodes to visit next. Here's a step-by-step process:

1. Enqueue the starting node.
2. Dequeue a node from the front of the queue.
3. Visit that node and enqueue all its unvisited neighbors.
4. Repeat until the queue is empty.

What are the applications of BFS in real-world scenarios?

BFS is used in various applications such as:

1. Finding the shortest path in unweighted graphs.
2. Web crawling.
3. Social networking applications to find connections.
4. Network broadcasting.

Are there any limitations to using BFS?

Yes, BFS can consume a lot of memory, especially for wide trees or graphs, as it stores all child nodes at the current level. It may also be slower than other algorithms like depth-first search in certain scenarios.