AlgoGenesis is a centralized open-source platform dedicated to providing optimized and well-documented algorithm implementations in C. Perfect for both beginners and advanced users, this repository serves as a comprehensive learning resource for solving algorithmic challenges.
I propose adding the A (A-star) algorithm to the AlgoGenesis collection. A is a crucial graph traversal algorithm that extends Dijkstra’s algorithm by incorporating a heuristic, making it highly efficient for pathfinding in real-world applications such as:
Game development: Used in AI for character movement (e.g., finding the shortest path between two points on a game map).
Robotics: Employed in robot navigation to compute optimal routes.
Navigation systems: Helps in dynamic route planning by considering real-time traffic or obstacles.
AI: Common in applications that involve decision-making and movement within large graphs.
The addition of A* will complement Dijkstra’s algorithm already in the repo, offering users a broader toolkit for solving shortest path problems in different scenarios.
Next Steps:
I plan to add a well-documented C implementation of the A* algorithm. Following that, I will include several examples and test cases that demonstrate:
How to use the algorithm on different graph types.
The difference between Dijkstra's and A in various scenarios.
Practical applications where A outperforms Dijkstra's in terms of speed and efficiency.
This will help developers easily understand how and when to use A*, especially in performance-critical applications.
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Let me know your thoughts! I'll be happy to proceed and provide a detailed breakdown. Please see appropriate level for doing so much . Thank you sir
Checklist:
:white_check_mark: Contributor in GSSoC-ext
:white_check_mark: Want to work on it
Additional Information:
Provide any other relevant information or resources regarding the algorithm.
Description:
I propose adding the A (A-star) algorithm to the AlgoGenesis collection. A is a crucial graph traversal algorithm that extends Dijkstra’s algorithm by incorporating a heuristic, making it highly efficient for pathfinding in real-world applications such as:
Game development: Used in AI for character movement (e.g., finding the shortest path between two points on a game map). Robotics: Employed in robot navigation to compute optimal routes. Navigation systems: Helps in dynamic route planning by considering real-time traffic or obstacles. AI: Common in applications that involve decision-making and movement within large graphs. The addition of A* will complement Dijkstra’s algorithm already in the repo, offering users a broader toolkit for solving shortest path problems in different scenarios.
Next Steps:
I plan to add a well-documented C implementation of the A* algorithm. Following that, I will include several examples and test cases that demonstrate:
How to use the algorithm on different graph types. The difference between Dijkstra's and A in various scenarios. Practical applications where A outperforms Dijkstra's in terms of speed and efficiency. This will help developers easily understand how and when to use A*, especially in performance-critical applications.
### Let me know your thoughts! I'll be happy to proceed and provide a detailed breakdown. Please see appropriate level for doing so much . Thank you sir
Checklist:
Additional Information:
Provide any other relevant information or resources regarding the algorithm.