This is a small project, visualizing simple implementation of MAPF by creating large state graph. It was done as a semestral project in Artificial Intelligence at my university.
- It generates all the possible state space with the possible configurations of the agents and creates a graph based on that.
- Then, uses A* on the state space graph to find better path based on Manhattan Distance on Heuristics and my custom G function for the "shortest" distance.
Simply clone this repo and install pygame library. Required: Python3, Pygame.
maps/ - contains simple test maps. They are configurable at init(filename) call at main.py.
pathfinding.py - util functions that handles parsing, A* algorithm, generation of state space.
main.py - the program to run. Scroll to the bottom and change the maps in init function.