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https://github.com/sunnyallana/astar-threaded-search

This repo implements A* search with multithreading for faster pathfinding.
https://github.com/sunnyallana/astar-threaded-search

astar-algorithm astar-pathfinding astar-search astar-search-algorithm operating-system

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This repo implements A* search with multithreading for faster pathfinding.

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## About This Repository

This repository hosts an implementation of the A* search algorithm using threads for parallel processing. A* (pronounced "A star") is a popular pathfinding algorithm commonly used in artificial intelligence and robotics for finding the shortest path between two points. By leveraging multithreading capabilities, this implementation enhances the efficiency of the A* algorithm, allowing it to explore potential paths concurrently.

### Key Features:
- **Threaded Processing**: Utilizes multiple threads to explore potential paths simultaneously, improving search performance on multicore systems.
- **Efficient Pathfinding**: Employs the A* algorithm to efficiently find the shortest path between two points on a graph or grid.
- **Configurable Parameters**: Allows customization of various parameters such as heuristic functions, thread count, and grid configurations to suit different use cases.
- **Clear Documentation**: Well-commented code and comprehensive documentation to aid understanding and further development.

### Usage:
1. **Clone Repository**: Clone this repository to your local machine.
2. **Compile**: Compile the source code using your preferred compiler with support for multithreading.
3. **Run**: Execute the compiled binary and specify the input parameters as needed.
4. **Explore**: Experiment with different configurations and parameters to observe performance variations.

### Contributions:
Contributions to this repository are welcome! Whether you want to optimize performance, add new features, or improve documentation, feel free to fork the repository and submit a pull request.

### License:
This project is licensed under the [MIT License](LICENSE), allowing for both personal and commercial use with proper attribution.