2048 ai,

🗣 SL提问: 2048 ai

✍️ Ai批改: The 2048 game!

2048 is a popular puzzle game where you slide numbered tiles on a grid to combine them and create a tile with the value of 2048、The game was created by Italian web developer Gabriele Cirulli in 2014.

To create an AI that plays 2048, we can use various techniques such as:

1、Minimax algorithm: a recursive algorithm that simulates all possible moves and their outcomes, evaluating the best move based on a heuristic function.
2、Expectimax algorithm: a variant of Minimax that takes into account the randomness of the tile spawns.
3、Greedy algorithm: a simple algorithm that chooses the move that maximizes the immediate gain.
4、Monte Carlo Tree Search (MCTS): a algorithm that uses random simulations to evaluate the best move.

Some common heuristics used to evaluate the game state are:

1、Monotonicity: the tendency of the tiles to be in a monotonic order (e.g., increasing or decreasing) in each row and column.
2、Smoothness: the difference between adjacent tiles.
3、Free tiles: the number of empty tiles on the grid.
4、Max tile: the value of the highest tile on the grid.

To implement a 2048 AI, we can use a programming language like Python、Here's a simple example using a Minimax algorithm:
python
import random

Game constants
GRID_SIZE = 4
GOAL_TILE = 2048

Heuristic function
def heuristic(grid):
Monotonicity
monotonicity = 0
for i in range(GRID_SIZE):
for j in range(GRID_SIZE 1):
if grid[i][j] grid[i][j + 1]:
monotonicity += 1
if grid[j][i] grid[j + 1][i]:
monotonicity += 1

Smoothness
smoothness = 0
for i in range(GRID_SIZE):
for j in range(GRID_SIZE 1):
smoothness += abs(grid[i][j] grid[i][j + 1])
smoothness += abs(grid[j][i] grid[j + 1][i])

Free tiles
free_tiles = sum(1 for row in grid for tile in row if tile == 0)

Max tile
max_tile = max(max(row) for row in grid)

return monotonicity + smoothness + free_tiles + max_tile

Minimax algorithm
def minimax(grid, depth):
if depth == 0 or game_over(grid):
return heuristic(grid)

best_score = -float('inf')
for move in ['up', 'down', 'left', 'right']:
new_grid = apply_move(grid, move)
if new_grid != grid:
score = -minimax(new_grid, depth 1)
best_score = max(best_score, score)

return best_score

Apply a move to the grid
def apply_move(grid, move):
new_grid = [row[:] for row in grid]
if move == 'up':
for j in range(GRID_SIZE):
tiles = [new_grid[i][j] for i in range(GRID_SIZE) if new_grid[i][j] != 0]
merged_tiles = merge_tiles(tiles)
new_grid[:, j] = merged_tiles + [0] * (GRID_SIZE len(merged_tiles))
elif move == 'down':
for j in range(GRID_SIZE):
tiles = [new_grid[i][j] for i in range(GRID_SIZE 1, -1, -1) if new_grid[i][j] != 0]
merged_tiles = merge_tiles(tiles)
new_grid[:, j] = [0] * (GRID_SIZE len(merged_tiles)) + merged_tiles[::-1]
elif move == 'left':
for i in range(GRID_SIZE):
tiles = [new_grid[i][j] for j in range(GRID_SIZE) if new_grid[i][j] != 0]
merged_tiles = merge_tiles(tiles)
new_grid[i, :] = merged_tiles + [0] * (GRID_SIZE len(merged_tiles))
elif move == 'right':
for i in range(GRID_SIZE):
tiles = [new_grid[i][j] for j in range(GRID_SIZE 1, -1, -1) if new_grid[i][j] != 0]
merged_tiles = merge_tiles(tiles)
new_grid[i, :] = [0] * (GRID_SIZE len(merged_tiles)) + merged_tiles[::-1]

return new_grid

Merge tiles
def merge_tiles(tiles):
merged_tiles = []
i = 0
while i < len(tiles):
if i + 1 < len(tiles) and tiles[i] == tiles[i + 1]:
merged_tiles.append(tiles[i] * 2)
i += 2
else:
merged_tiles.append(tiles[i])
i += 1
return merged_tiles

Game over condition
def game_over(grid):
for i in range(GRID_SIZE):
for j in range(GRID_SIZE):
if grid[i][j] == GOAL_TILE:
return True
if grid[i][j] == 0:
return False
return True

Main AI loop
def ai(grid):
best_move = None
best_score = -float('inf')
for move in ['up', 'down', 'left', 'right']:
new_grid = apply_move(grid, move)
if new_grid != grid:
score = minimax(new_grid, 5)
if score best_score:
best_score = score
best_move = move
return best_move

Example usage
grid = [[2, 0, 0, 0],
[0, 2, 0, 0],
[0, 0, 4, 0],
[0, 0, 0, 2]]

while True:
move = ai(grid)
print(fMove: {move})
grid = apply_move(grid, move)
print(grid)
Add a new tile to the grid
grid[random.randint(0, GRID_SIZE 1)][random.randint(0, GRID_SIZE 1)] = 2
if game_over(grid):
break

This is a basic example, and there are many ways to improve it (e.g., using a more advanced heuristic, optimizing the Minimax algorithm, etc.).

Do you have any specific questions about implementing a 2048 AI or would you like to discuss any particular aspect of the game?