These are the two strategies which are quite similar. In best first search, we expand the nodes in accordance with the evaluation function. While, in breadth first search a node is expanded in accordance to the cost function of the parent node.
Breadth First Search (BFS) and Best First Search (BFS) are two fundamental search algorithms used in artificial intelligence, particularly in problem-solving tasks like pathfinding or searching through large state spaces. Here are the main differences between the two:
- Search Strategy:
- Breadth First Search explores all the neighbor nodes at the present depth prior to moving on to the nodes at the next depth level. It traverses the tree horizontally.
- Best First Search selects the node which is the most promising among all the nodes available in the search space. It evaluates each node based on a heuristic function that estimates the “goodness” of that node.
- Optimality:
- BFS is complete and optimal if the branching factor is finite and the cost per step is the same. It guarantees finding the shortest path from the starting node to the goal node.
- Best First Search does not guarantee optimality, as it selects the most promising node based on the heuristic evaluation, which may not necessarily lead to the optimal solution. It can be efficient in finding solutions in large search spaces but does not guarantee the shortest path.
- Memory Usage:
- BFS requires a lot of memory because it has to store all the nodes at each depth level in memory until it reaches the goal node or exhausts the entire search space.
- Best First Search may require less memory compared to BFS because it only needs to store the most promising nodes based on the heuristic function.
- Time Complexity:
- BFS has a time complexity of O(b^d), where b is the branching factor and d is the depth of the shallowest goal node. This can be quite high if the branching factor is large.
- Best First Search time complexity depends largely on the quality of the heuristic function. In the worst case, it can be exponential, but with a good heuristic, it can be much more efficient than BFS.
In summary, BFS is a systematic and exhaustive search strategy that ensures optimality but can be memory-intensive, while Best First Search is heuristic-driven, which may sacrifice optimality but can be more memory and time-efficient, especially in large search spaces.