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Posts Tagged ‘Goal node (computer science)’

A* Search

September 4th, 2010 No comments
An example of A star (A*) algorithm in action ...

Image via Wikipedia

A* uses a best-first search and finds the least-cost path from a given initial node to one goal node (out of one or more possible goals).

It uses a distance-plus-cost heuristic function (usually denoted f(x)) to determine the order in which the search visits nodes in the tree. The distance-plus-cost heuristic is a sum of two functions:

  • The path-cost function, which is the cost from the starting node to the current node (usually denoted g(x))
  • In addition, an admissible “heuristic estimate” of the distance to the goal (usually denoted h(x)).

Depth First Search

September 4th, 2010 No comments

Depth First Search

Depth First Search

Formally, DFS is an uninformed search that progresses by expanding the first child node of the search tree that appears and thus going deeper and deeper until a goal node is found, or until it hits a node that has no children. Then the search backtracks, returning to the most recent node it has not finished exploring. In a non-recursive implementation, all freshly expanded nodes are added to a stack for exploration.