Python-based system using reusable pathfinding algorithms to solve multiple games via a common Graph interface. Easily extensible for new games.
- Implemented pathfinding algorithms (DLS, BFS, IDDFS, HillClimb).
- Initialized and implemented the idea of unified graph solver algorithms.
- Implemented sudoku game graph by assigning each empty box to its all possible number, and the goal is the box with exactly one possible choice.
- Implemented 8 queens game graph by generating each possible position for all 8 queens inside the 8x8 board, and the goal is a valid 8 queens board.
- Implemented Maze game graph by generating a new random maze then turning all possible moves from the start to the goal into a graph.
- Built both CLI/GUI testing environments with unified interfaces.
- Documented the project by providing detailed explanations of various AI search and optimization algorithms, including their advantages, limitations, and applications.
- Created structured overviews of algorithms such as Hill Climbing, Minimax, Alpha-Beta Pruning, BFS, IDDFS, DLS, and A*.
- Explained algorithm implementations with step-by-step breakdowns, including key code snippets to demonstrate their functionality.
- Outlined real-world applications of the implemented algorithms, linking them to areas like game AI, robotics, optimization, and machine learning.
- Designed a clear problem breakdown for challenges like the Maze Problem, defining its constraints, solution strategies, and performance evaluation criteria.
- Provided code explanations for core components such as graph representation, pathfinding strategies, and heuristic-based decision-making.
- Compiled relevant external resources to support further learning and research on the algorithms used in the project.
- python
- tkinter
- customkinter
- GitHub for version control
- Claude 3.5 Sonnet for building most GUI blocks.
In order to run the project run the "Main Screen.py" file found in the UI Folder , Thats it!




