minmax algorithm for conway's game of life in matlab

main.m
function [bestRow, bestCol, bestVal] = Minimax(gameBoard, player, depth)
% Minimax algorithm for Game of Life
% gameBoard - 2D matrix representing the current board state
% player - current player (1 or -1)
% depth - current depth of the search tree
% returns the best row, column, and value

if depth == 0
    % evaluate the board at the current position
    bestVal = EvaluateBoard(gameBoard);
    bestRow = -1;
    bestCol = -1;
else
    % find all possible moves
    moves = PossibleMoves(gameBoard, player);
    numMoves = size(moves, 1);
    bestVal = -Inf;
    
    for i = 1:numMoves
        % make the move
        gameBoard(moves(i, 1), moves(i, 2)) = player;
        
        % recursive call to search deeper
        [tempRow, tempCol, tempVal] = Minimax(gameBoard, -player, depth-1);
        
        % undo the move
        gameBoard(moves(i, 1), moves(i, 2)) = 0;
        
        % update the best move
        if -tempVal > bestVal
            bestVal = -tempVal;
            bestRow = moves(i, 1);
            bestCol = moves(i, 2);
        end
    end
end
end

function val = EvaluateBoard(gameBoard)
% evaluate the board at the current position
val = sum(sum(gameBoard));
end

function moves = PossibleMoves(gameBoard, player)
% find all possible moves
[m, n] = size(gameBoard);
moves = [];

for i = 1:m
    for j = 1:n
        if gameBoard(i, j) == 0
            % empty cell - check if it leads to a new live cell
            newBoard = gameBoard;
            newBoard(i, j) = player;
            if sumNeighbours(i, j, newBoard) == 3
                moves = [moves; i j];
            end
        end
    end
end
end

function num = sumNeighbours(row, col, gameBoard)
% sum the values of the neighbouring cells
[m, n] = size(gameBoard);
num = 0;

for i = -1:1
    for j = -1:1
        if ~(i == 0 && j == 0)
            r = mod(row+i-1, m)+1;
            c = mod(col+j-1, n)+1;
            num = num + gameBoard(r, c);
        end
    end
end
end
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