This repository contains a project where A* searching algorithm is implemented and visualized using the Kivy GUI.
The learning goals for this project was to understand and learn how to implement the A* searching algorithm. The A* algorithm essentially works by minimizing a function f(n) = g(n) + h(n) where g(n) represents the cost function to the node n and h(n) is the heuristic of the node n. Moreover, in this project, the distances are computed using Manhattan distance and so g(n) is basically the number of nodes that it travelled through to get to node n and h(n) is the Manhattan distance from the current node to the final goal node.
The other main learning objective of this project was to use and understand Kivy for the first time. Kivy is more powerful than Pygame when it comes to GUI and simple game development but is also much more complicated to use due to the class inheritance. A main desirable feature of Kivy is how easy it is to convert the application into an android application.
- main.py contains all the necessary code for the A* search and the Kivy application.
- Astar.kv contains the kivy file for the App. This is still a work in progress.
- The A* searching algorithm is completed. The A* searching algorithm was rewritten almost entirely, and it now works much better with no (known) bugs.
- The Kivy GUI is functional but there is still a lot of potential work to be done. For instance, creating multiple windows such as an intro window and an ending window.
- I also want to introduce new features such as being able to change the include_diag boolean within the GUI and also having a flexible number of walls and a start button.