$1$ Summary

$$ Develop a competitive AI for the game Mancala

$$ Demonstrate your understanding of the MiniMax search algorithm, alpha$-$

beta pruning, and dynamic programming

We will be using Python $3$ so be sure you aren$$t using older versions. Code

that will compile in Python $2\mathrm{.}7$ may not compile in Python $3.$ Please write

down your group No$.$ and teammates$$ names.

$2$ Background

Mancala is a two$-$player, turn$-$based strategy game where the objective is to

collect the most pieces by the end of the game. To play a game, you need a

Mancala board, which is a board made up of two rows of six pockets, also

known as pits, and two $$stores$$ located at the ends of these pits.

$2\mathrm{.}1$ Rules

$1.$ Each turn consists of a player picking up all the pieces in a pit and, moving

counter$-$clockwise, depositing a stone in each pocket until the stones run

out. When moving your stones, if you pass your store then you deposit

one stone inside it as well, but you skip over your opponent$$s store.

$2.$ If the last piece you place goes into your store, you take another turn.

$3.$ If the last piece you place is in an empty space on your side, and your

opponent has stones in the pit exactly opposite of this empty space$1,$ then

you collect all the stones in your opponent$$s opposite pit as well as your

last placed stone.

$4.$ The game is over when all the stones on one side of the board are gone,

and when this happens the other player takes all the stones on their side

and puts them in their store.

$1$Note that this rule differs slightly from the rules linked, which do not require your

opponent have stones in their pit to make an $$empty capture$.$ However, this is consistent

with the interactive website linked, and with how the game is most often played.

$1$