In 1968, Stanford Research Institute (now SRI International) researchers Peter Hart, Nils Nilsson, and Bertram Raphael published the algorithm. 

A* is a complete, optimum, efficient graph traversal and path search algorithm in many computer science domains. Since it saves all created nodes in memory, it is space-intensive. Thus, in practical travel-routing systems, it is usually surpassed by algorithms that pre-process the graph and memory-bounded techniques, but A* is often the best answer.

A* search significance

A* Search Algorithm is a straightforward and efficient search algorithm for determining the best path between two nodes in a graph. It will be utilized to find the shortest path. Dijkstra's shortest path algorithm (Dijkstra's Algorithm) is an extension of it.

The A* Search Algorithm additionally employs a heuristic function, which provides additional information about how distant we are from the objective node. This function is used with the f-heap data structure to improve searching efficiency.

A* search algorithm

Step 1: Add the first node to the OPEN list.
Step 2: Determine whether the OPEN list is empty; return failure and stop.
Step 3: Choose the node from the OPEN list with the shortest value of the evaluation function (g+h); if node n is the goal node, return success and stop; otherwise, return failure and stop.
Step 4: Extend node n and generate its descendants, then add n to the closed list. Check whether each successor n' is already in the OPEN or CLOSED list; if not, compute an evaluation function for n' and insert it in the Open list.
Step 5: If node n' is already in OPEN and CLOSED states, it should be attached to the back pointer containing the lowest g(n') value.
Step 6: Go back to Step 2.

Algorithm source: Javatpoint

Use Cases

A* has been used successfully in a variety of real-world circumstances. In robotic path planning, for example, A* assists robots in navigating across dynamic situations while avoiding obstacles. A* generates clever adversary AI to efficiently chase and follow the in-game player creation. In logistics and transportation, A* assists in determining the best routes for delivery vehicles to save time and money. A* also has network routing applications, such as finding the shortest path in a computer network. These examples demonstrate the flexibility and applicability of A* algorithm concepts and implementations in various applications.

Applications

The A* method is frequently used for pathfinding and optimization issues in many disciplines. Robotics, video games, route planning, logistics, and AI use it. In robotics, A* assists robots in navigating obstacles and determining ideal courses. It allows NPCs in video games to navigate game surroundings intelligently. A* is used by route planning apps to discover the shortest or fastest route between two points. A* is used in the logistics industry for vehicle routing and scheduling. A* optimizes AI decision-making in natural language processing and machine learning. Its adaptability and efficiency make it a practical algorithm in various real-world circumstances.

Image source: Unsplash