Which type of best first search algorithm was used to predict the closeness of the end of path and its solution?

Question

Accepted Answer

The correct option is (1):
Greedy Best-First Search (Greedy BFS) is the specific type of informed search algorithm designed to prioritize nodes based purely on their estimated proximity to the goal. The evaluation function it employs, $f(n)$, is defined strictly as the heuristic function, $h(n)$, where $h(n)$ provides an estimate of the cost from the current node $n$ directly to the goal state (the solution). This "greedy" strategy expands the node that looks closest to the goal at any given moment, making it the algorithm most accurately associated with predicting the "closeness of the end of path and its solution." Its primary objective is speed, often sacrificing optimality by disregarding the actual cost incurred from the start node to the current node.

The incorrect option is (2):
Divide and Conquer is an algorithmic paradigm, not a specific search algorithm like Best-First Search. This paradigm involves breaking a problem down into smaller subproblems, solving those subproblems recursively, and then combining their solutions. Examples include algorithms like Merge Sort and Quick Sort. It is a general problem-solving approach and does not rely on a goal-closeness heuristic to navigate a state space, which is the core function described in the question.

The incorrect option is (3):
Heuristic BFS is a broad, generic category that describes any Best-First Search algorithm utilizing a heuristic function, $h(n)$, to guide its search. This category encompasses both Greedy BFS and the A\* search algorithm. While technically correct that Greedy BFS is a heuristic BFS, the question asks for the specific *type* of algorithm whose method is defined by predicting "closeness." Since Greedy BFS is the specific variant that uses *only* the heuristic function for this prediction, it is the more precise and intended answer compared to the general term "Heuristic BFS."

The incorrect option is (4):
Combinatorial refers to a class of problems in mathematics and computer science that involve finding an optimal object (like the shortest path) from a finite set of possibilities. While pathfinding is an example of a combinatorial search problem, this term describes the *nature of the problem* being solved (the domain) rather than the *specific mechanism* of the Best-First Search algorithm used to solve it. It is a classification of the problem space, not a type of search algorithm or a function used for closeness prediction.