Authors: Lucas (Engine), Daniel (Board Logic), Althea (GUI), Niko (TUI)
This respository contains a design and implementation for big checkers (a general implementation of Checkers).
Our implementation uses the following libraries that may need installing:
rich
pygame
click
You can install these with
pip install rich pygame click
To run the TUI, navigate to the root of the repository, and run
python3 src/tui.py
When opened, the user will be faced with a series of questions, asking them to help set up the game. Questions will ask the user what the types of the two players are (either "Human", "Random Bot", or "Smart Bot"), the board size (int between 1 and 12), and in the case where a Smart Bot was selected, what depth the bot should run at.
The user should note that complexity increases with increased board size and increased smart bot depth. As such, we recommend that on board sizes >4, bot depth should not exceed 2. On board sizes <=4, one can try using a higher depth, but should expect slower runtimes.
The TUI displays a representation of the board and asks for a human player's next move. Players input moves according to the axes of the board. For example,
a|1
asks the tui to move the piece at a|1. Then, the TUI will prompt the player
to input the location where the piece is moving to. In the case of a
multi-jump move, this may happen multiple tim
If at any time the location input is not valid, the TUI will prompt again for a correct move.
If for any reason one needs to exit the game, inputting exit will accomplish
this.
A Human player can offer a draw by inputting draw. Bots always accept draw
offers, while a Human opponent is prompted to accept of not accept the draw.
A Human player can resign by inputting resign.
Once the game finishes, one can replay by typing
python3 src/tui.py
into the terminal again.
Canonically, Black (displayed blue because dark terminals are popular) plays first: see American Checkers. As such, we have black play first as well.
To stimulate two bots playing against each other multiple times, run
python3 src/bot_minimax.py
You will be prompted with instructions on how to play the two bots against one another (random, smart, depth, number of games) and you will recieve the game outcomes as percentages.