A* search is a graph traversal algorithm that is used to find the shortest path between two nodes in a graph. The algorithm works by iteratively expanding the search frontier, which is a set of nodes that have not yet been explored. At each step, the algorithm adds the node with the lowest estimated cost to the search frontier.
The estimated cost of a node is the sum of the cost of reaching the node from the start node and the estimated cost of reaching the goal node from the node. The estimated cost of the goal node is always 0.
The A* search algorithm is guaranteed to find the shortest path between two nodes in a graph if the estimated cost function is admissible, which means that the estimated cost of a node is never less than the actual cost of the node.
A* search is a very efficient algorithm for finding the shortest path between two nodes in a graph. The algorithm is often used in pathfinding problems, such as finding the shortest path from a robot's current location to its goal location.
Advantages of A Search*
A* search is a very efficient algorithm for finding the shortest path between two nodes in a graph.
A* search is a very well-understood algorithm, and there are a number of different variations that can be used to improve its performance.
A* search is relatively easy to implement.
Disadvantages of A Search*
A* search can be computationally expensive to run, especially for large graphs.
A* search can be very slow to converge, especially for graphs with a large number of nodes.
A* search can be very difficult to implement for complex graphs.