Best-First Search Algorithm
Best-first search is a systematic control strategy, combining the strengths of breadth-first and depth-first search into one algorithm. The main difference between best-first search and the brute-force search techniques is that we make use of an evaluation or heuristic function to order the SearchNode objects on the queue. In this way, we choose the SearchNode that appears to be best, before any others, regardless of their position in the tree or graph.
It tries to expand the node that is closest to the goal, on the grounds that this is likely to lead to a solution quickly. Thus, it evaluates nodes by using just the heuristic function: f (n) = h(n).
Characteristics of Best First Search
• Like the depth-first and breadth-first search, best-first search uses two-lists. open: to keep track of the frontier of the search. closed: to record states already visited.
• Order the states on open according to some heuristic estimate of their closeness to a goal.
• At each iteration through the loop, consider the most promising state on the open list next.
• When visiting a child state, if it is already on open or closed, the algorithm checks if the child is reached by a shorter path this time compared with the last time it arrived at this child.
المادة المعروضة اعلاه هي مدخل الى المحاضرة المرفوعة بواسطة استاذ(ة) المادة . وقد تبدو لك غير متكاملة . حيث يضع استاذ المادة في بعض الاحيان فقط الجزء الاول من المحاضرة من اجل الاطلاع على ما ستقوم بتحميله لاحقا . في نظام التعليم الالكتروني نوفر هذه الخدمة لكي نبقيك على اطلاع حول محتوى الملف الذي ستقوم بتحميله .
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