AI News, Artificial Intelligence/Search/Heuristic search/Bidirectional Search

Artificial Intelligence/Search/Heuristic search/Bidirectional Search

Bidirectional search is an algorithm that uses two searches occurring at the same time to reach a target goal.

Bidirectional search generally appears to be an efficient graph search because instead of searching through a large tree, one search is conducted backwards from the goal and one search is conducted forward from the start.

The reason that this is faster is because the trees grow exponentially by their depth and therefore two smaller trees have a smaller area than one large tree.

The section of the search before they meet is called the main phase and after the intersection, it is called the post processing phase.It is important to note that most many bidirectional searches use a heuristic which means that there is no way to confirm whether the solution that is found is the most optimal solution.

The algorithm of a graph search goes through nodes in a graph systematically until an optimal solution is found whereas a heuristic search will only confirm some kind of solution in a short amount of time.

Using the idea suggested from Champeaux’s model, Politowisky and Pohl used a front to front design where the start node's pathway aims at the most promising node of the goal's pathway and vice versa.

The 15-puzzle consists of a board of tiles with random numbers placed on them and the search system must go through and place the tiles in order.

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