Hard-to-beat minimax algorithm computer opponent.
Tick off requirements as you build to track real-time completion.
Follow this chronological guide to build the project from scratch.
Implement recursive minimax state checking to return the highest potential score coordinates.
def minimax(board, depth, is_maximizing):
score = evaluate_board(board)
if score == 10: return score - depth
if score == -10: return score + depth
if not empty_cells_remain(board): return 0
if is_maximizing:
best = -1000
for move in get_empty_moves(board):
make_move(board, move, 'O')
best = max(best, minimax(board, depth+1, False))
undo_move(board, move)
return best
else:
best = 1000
for move in get_empty_moves(board):
make_move(board, move, 'X')
best = min(best, minimax(board, depth+1, True))
undo_move(board, move)
return bestReal issues students hit during development and how to troubleshoot them fast.
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