Rh17S15/TicTacToe
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Revert "Added Alpha-Beta-Pruning to Speed up AI to minimax"

Browse Source 
This reverts commit 23d8207e62adef9f57d12461e651dba7567a185f.
This commit is contained in:
Rh17S15
2025-09-22 19:43:52 +02:00
parent a4ea1a2ec8
commit 324564d6dc
1 changed files with 3 additions and 7 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10
MVC/minimax.py
View File

@@ -4,7 +4,7 @@ import random
class Minimax: class Minimax:
def minimax(self, current_field, is_maximizing, player1_char, player2_char, alpha=float('-inf'), beta=float('inf')): def minimax(self, current_field, is_maximizing, player1_char, player2_char):
checkwin = self.check_win(current_field, player1_char, player2_char) checkwin = self.check_win(current_field, player1_char, player2_char)
if checkwin == (1, 1): # Draw if checkwin == (1, 1): # Draw
return 0, 0, 0 return 0, 0, 0
@@ -20,20 +20,15 @@ class Minimax:
for k in range(0, len(current_field), 2): for k in range(0, len(current_field), 2):
if current_field[j][k] == " ": if current_field[j][k] == " ":
current_field[j][k] = player1_char if not is_maximizing else player2_char current_field[j][k] = player1_char if not is_maximizing else player2_char
score = self.minimax(current_field, not is_maximizing, player1_char, player2_char, alpha, beta)[0] score = self.minimax(current_field, not is_maximizing, player1_char, player2_char)[0]
current_field[j][k] = " " current_field[j][k] = " "
if is_maximizing and score > best_score: if is_maximizing and score > best_score:
best_score = score best_score = score
best_move = j, k best_move = j, k
alpha = max(alpha, best_score)
elif not is_maximizing and score < best_score: elif not is_maximizing and score < best_score:
best_score = score best_score = score
best_move = j, k best_move = j, k
beta = min(beta, best_score)
if beta <= alpha:
break # Beta cutoff
if best_score == 0 and best_move == (0, 0): # is None: if best_score == 0 and best_move == (0, 0): # is None:
empty_cells = [(j, k) for j in range(0, len(current_field), 2) for k in range(0, len(current_field), 2) if empty_cells = [(j, k) for j in range(0, len(current_field), 2) for k in range(0, len(current_field), 2) if
@@ -45,6 +40,7 @@ class Minimax:
if best_move is None: if best_move is None:
return 0, -1, -1 # No available moves return 0, -1, -1 # No available moves
else: else:
# print('The next best move is:', best_move, "score: ", best_score)
return best_score, best_move[1], best_move[0] return best_score, best_move[1], best_move[0]
def check_win(self, ifield, player1_char, player2_char): def check_win(self, ifield, player1_char, player2_char):