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Search Algorithm — A* Search, with Python
Exploring A* Heuristic Search with Hands-On Python Examples
A* Search (A-star) is a widely used and highly effective algorithm for finding the shortest path in a graph. It is popular because it combines efficiency, accuracy, and conceptual simplicity.
Whether you are learning algorithms, preparing for technical interviews, or building navigation and optimization systems, A* is one of the most important search techniques to understand.
This article explains the intuition behind A*, its relationship with classical search algorithms, and demonstrates a practical Python implementation using the Romania map problem.
Background: Where A* Comes From
A* Search is built by combining two classical search strategies:
1. Uniform-Cost Search (UCS)
Uniform-Cost Search uses the path-cost function g(n), which represents the cost accumulated so far to reach node n (past experience).
- Optimal and complete, i.e., always finds the best solution if one exists.
- However, it can be inefficient, as it explores widely without guidance.
