### A* Pathfinding Algorithm in JavaScript

In the realm of pathfinding algorithms, the A* algorithm stands out as a versatile and efficient method for finding the shortest path between two points on a grid. This blog post will delve into the inner workings of the A* algorithm, using JavaScript as the language of choice for our implementation. We'll explore the key components of the algorithm and provide snippets of the source code to illustrate its functionality.

## Demo

https://adamstirtan.github.io/astar-js/

## Overview of the A* Algorithm

A* (pronounced "A star") is a heuristic search algorithm commonly used in various applications, such as robotics, video games, and geographical information systems. It efficiently finds the optimal path from a start point to an end point while considering the cost of movement and avoiding obstacles.

The algorithm maintains two sets: the open set and the closed set. The open set contains nodes to be evaluated, while the closed set contains nodes that have already been evaluated. A* uses a combination of the cost to reach a node (g), the heuristic estimate from the node to the goal (h), and the total cost (f = g + h) to prioritize nodes for evaluation.

Let's take a closer look at the core implementation of the A* algorithm in JavaScript:

## Key Components to A*

- Open and Closed Sets: The algorithm maintains two sets. The open set contains nodes to be evaluated, and the closed set contains nodes that have already been evaluated.
- Total Cost Calculation (f): A* calculates the total cost (f) of each node by combining the cost to reach the node (g) and the heuristic estimate to the goal (h).
- Priority Queue: Nodes in the open set are prioritized based on their total cost (f). The algorithm selects the node with the lowest total cost for evaluation.
- Heuristic Function: The heuristic function estimates the cost from a node to the goal. In our example, we use the Manhattan distance as the heuristic.
- Neighboring Nodes: A* explores neighboring nodes in four directions (right, down, left, up). It considers valid and unexplored neighbors while avoiding obstacles.

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