The A-Star Algorithm A Pathfinding Powerhouse
Introduction
Algorithms for pathfinding are fundamental to a variety of applications, from the AI in games to the robotics and GPS navigation of today. The most efficient and widely used pathfinding algorithm seems to be the A* (A-Star) algorithm. In this post, we’re going to explore how the A* algorithm works, its advantages, and why it’s the optimal go-to choice for pathfinding when "GPS" stands for "Graph Parsing System."
♠What is the A* Algorithm?
The algorithm A* is a search algorithm that finds the shortest route from a start node to a goal node. It takes the good features of Dijkstra's Algorithm (which guarantees the shortest path) and the Greedy Best-First Search (which uses heuristics to speed up the process) and combines them. The result is an algorithm that is both optimal and efficient.
♠How Does A* Work?
A* has two main cost functions that it works with:
g(n) – The real cost from the start node to the current node.
h(n) – The estimated cost from the current node to the goal (heuristic function).The function employed to evaluate the nodes is as follows:
total cost = f(n) = g(n) + h(n)
It picks the node that has the lowest f(n) value and expands it, carrying on with this literal interpretation of the instructions until it reaches the goal.
♠The Heuristic Function (h(n))
A*'s efficiency hinges on choosing a good heuristic function. Heuristics commonly used include:
- Manhattan Distance (for grids with movement constrained to horizontal and vertical directions)
- Euclidean Distance (for movement allowed in any direction)
- Diagonal Distance (for when diagonal movement is permitted)
♠Advantages of A*
When the heuristic is both admissible and consistent, the following can be guaranteed:
- The path found will be the shortest.
- The algorithm is more efficient than Dijkstra's in most cases.
- It is widely used in AI, robotics, game development, and so on.
♠Implementation of A*
I have attached the link to github code implemented and visualised using p5 and a link to a live demo.
GITHUB: https://github.com/sappiah085/A-algorithm-in-typescript
LIVE DEMO: https://realmannthought.netlify.app/project/AStar-Algorithm
Conclusion
The A* algorithm remains a basic and useful tool for pathfinding and mapping. It has an optimal balance between speed and accuracy. The reason is that it uses the heuristic very carefully.
What is your opinion of the A* algorithm? Have you applied it to any of your work? Let’s have a conversation about it in the comments!
