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funcs/games/hex.py

@@ -247,43 +247,25 @@ def hexAI(channel):
     
     board = data[channel]["board"]
     difficulty = data[channel]["difficulty"]
-    """ 
-    if len(data[channel]["gameHistory"]):
-        lastMove = data[channel]["gameHistory"][-1]
-    else:
-        lastMove = (5,5)
-    
-    # These moves are the last move +- 2. 
-    moves = [[(lastMove[0]+j-2,lastMove[1]+i-2) for i in range(5) if lastMove[1]+i-2 in range(11)] for j in range(5) if lastMove[0]+j-2 in range(11)]
-    moves = sum(moves,[])
-    chosenMove = None
-    safety = 0
-    while chosenMove == None:
-        safety += 1
-        if safety > 1000: 
-            break
-        candidate = random.choice(moves)
-        if board[candidate[0]][candidate[1]] == 0:
-            chosenMove = candidate
-    logThis("Last move was "+str(lastMove))
-    logThis("Chosen move is "+str(chosenMove)) """
-
     possiblePlaces = [i for i,v in enumerate(sum(board,[])) if v == 0]
     judgements = [-math.inf]*len(possiblePlaces) # All possible moves are yet to be judged
+    GwenColor = data[channel]["players"].index("Gwendolyn") + 1 # either 1 or 2 - red or blue
 
+    current_score = evaluateBoard(board)[0]
     for i in possiblePlaces:
         testBoard = copy.deepcopy(board)
         testBoard[i // BOARDWIDTH][i % BOARDWIDTH] = 1
+        if evaluateBoard(testBoard)[0] != current_score: # only think about a move if it improves the score (it's impossible to get worse)
             # Testing a move and evaluating it
-        judgements[i] = minimaxHex(testBoard,difficulty,-math.inf,math.inf,False)
+            judgements[i] = minimaxHex(testBoard,difficulty,-math.inf,math.inf,GwenColor==2)
             logThis("Best score for place {} is {}".format((i // BOARDWIDTH,i % BOARDWIDTH),judgements[i]))
 
-    GwenColor = data[channel]["players"].index("Gwendolyn") + 1
     bestScore = max(judgements) if (GwenColor == 1) else min(judgements)
     indices = [i for i, x in enumerate(judgements) if x == bestScore] # which moves got that score?
     i = random.choice(indices)
     chosenMove = (i // BOARDWIDTH , i % BOARDWIDTH)
     placement = "abcdefghijk"[chosenMove[1]]+str(chosenMove[0]+1)
+    logThis("ChosenMove is {} at {}".format(chosenMove,placement))
     return placeHex(channel,placement, "Gwendolyn")
 
 
@@ -292,7 +274,6 @@ def evaluateBoard(board):
     winner = 0
     # Here, I use Dijkstra's algorithm to evaluate the board, as proposed by this article: https://towardsdatascience.com/hex-creating-intelligent-adversaries-part-2-heuristics-dijkstras-algorithm-597e4dcacf93
     for player in [1,2]:
-        logThis("Running Dijkstra for player "+str(player))
         Distance = copy.deepcopy(EMPTY_DIJKSTRA)
         # Initialize the starting hexes. For the blue player, this is the leftmost column. For the red player, this is the tom row. 
         for start in (ALL_POSITIONS[::11] if player == 2 else ALL_POSITIONS[:11]):
@@ -329,12 +310,13 @@ def evaluateBoard(board):
 def minimaxHex(board, depth, alpha, beta, maximizingPlayer):
     # The depth is how many moves ahead the computer checks. This value is the difficulty. 
     if depth == 0 or 0 not in sum(board,[]):
-        score = evaluateBoard(board)
+        score = evaluateBoard(board)[0]
         return score
     # if final depth is not reached, look another move ahead:
     if maximizingPlayer: # red player predicts next move
         maxEval = -math.inf
         possiblePlaces = [i for i,v in enumerate(sum(board,[])) if v == 0]
+        #logThis("Judging a red move at depth {}".format(depth))
         for i in possiblePlaces:
             testBoard = copy.deepcopy(board)
             testBoard[i // BOARDWIDTH][i % BOARDWIDTH] = 1 # because maximizingPlayer is Red which is number 1
@@ -347,6 +329,7 @@ def minimaxHex(board, depth, alpha, beta, maximizingPlayer):
     else: # blue player predicts next move
         minEval = math.inf
         possiblePlaces = [i for i,v in enumerate(sum(board,[])) if v == 0]
+        #logThis("Judging a blue move at depth {}".format(depth))
         for i in possiblePlaces:
             testBoard = copy.deepcopy(board)
             testBoard[i // BOARDWIDTH][i % BOARDWIDTH] = 2 # because minimizingPlayer is Blue which is number 2