This checkers endgame solver finds the optimal moves for a given checkers endgame position in order to win.
The solver uses the minimax algorithm with alpha-beta pruning to find the optimal moves. Node ordering is implemented so that maximum pruning occurs. The solver also uses state caching, which allows the solver to check if a given state is already in the cached dictionary, reducing repetitive evaluations of states.
- Clone the repository and navigate to the directory
- Use the following command, specifying the necessary input files and the output file:
python checkers.py --inputfile <input file> --outputfile <output file>
- Replace
<input file>with an input board state file. - Replace
<output file>with the new output file name.
If we have the starting checkers board state board1.txt, and we want the optimal solution for the red player output to output.txt, we would run the following command:
python checkers.py --inputfile board1.txt --outputfile output.txt
- A checkers board state is a grid of 64 characters, with eight rows and eight characters per row.
- ’.’ is an empty square.
- ’r’ is a red piece,
- ’b’ is a black piece,
- ’R’ is a red king,
- ’B’ is a black king.