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Dijkstra's algorithm, as another example of a uniform-cost search algorithm, can be viewed as a special case of A* where = for all x. [ 12 ] [ 13 ] General depth-first search can be implemented using A* by considering that there is a global counter C initialized with a very large value.
LPA* maintains two estimates of the start distance g*(n) for each node: . g(n), the previously calculated g-value (start distance) as in A*; rhs(n), a lookahead value based on the g-values of the node's predecessors (the minimum of all g(n' ) + d(n' , n), where n' is a predecessor of n and d(x, y) is the cost of the edge connecting x and y)
Dijkstra's algorithm; A* search algorithm, a special case of the Dijkstra's algorithm; D* a family of incremental heuristic search algorithms for problems in which constraints vary over time or are not completely known when the agent first plans its path
The path found by A* on an octile grid vs. the shortest path between the start and goal nodes. Any-angle path planning algorithms are pathfinding algorithms that search for a Euclidean shortest path between two points on a grid map while allowing the turns in the path to have any angle.
In computer science, jump point search (JPS) is an optimization to the A* search algorithm for uniform-cost grids. It reduces symmetries in the search procedure by means of graph pruning, [1] eliminating certain nodes in the grid based on assumptions that can be made about the current node's neighbors, as long as certain conditions relating to the grid are satisfied.
SMA* or Simplified Memory Bounded A* is a shortest path algorithm based on the A* algorithm. The main advantage of SMA* is that it uses a bounded memory, while the A* algorithm might need exponential memory. All other characteristics of SMA* are inherited from A*.
The search algorithm uses the admissible heuristic to find an estimated optimal path to the goal state from the current node. For example, in A* search the evaluation function (where is the current node) is: = + where = the evaluation function.
In computer science, anytime A* is a family of variants of the A* search algorithm.Like other anytime algorithms, it has a flexible time cost, can return a valid solution to a pathfinding or graph traversal problem even if it is interrupted before it ends, by generating a fast, non-optimal solution before progressively optimizing it.