The node which is closest to goal will be expanded first. Although, explanation of nodes depends upon f(n) = h(n). Further, using priority queue we implement it.
Disadvantage
- It can get stuck in loops. It is not optimal.
In an interview setting, a concise yet comprehensive answer to the question “What is the Greedy Best First Search Algorithm?” might be:
“Greedy Best First Search is a heuristic search algorithm used in artificial intelligence for traversing/searching a graph or tree. Unlike traditional breadth-first or depth-first search algorithms, which explore all possible paths exhaustively, Greedy Best First Search selects the path that appears most promising at each step, based on a heuristic evaluation function. This function estimates the potential of each node to lead to the goal state. The algorithm iteratively expands the node with the lowest heuristic value, prioritizing nodes that are closer to the goal. While efficient in certain scenarios, Greedy Best First Search does not guarantee optimality and may get stuck in local optima.”
This answer provides a clear definition of the algorithm, its purpose, key characteristics, and limitations, demonstrating both understanding and communication skills.