From a093060b0e8a787e51212b5f2879dc839605da65 Mon Sep 17 00:00:00 2001 From: Matt Strapp Date: Mon, 26 Apr 2021 17:12:01 -0500 Subject: Revert "Refactor jsut about everything" This reverts commit e58a60ed18bde5db28ba96910df518a61b3999b2. --- dotsandboxes/agents/algorithms/alphaBeta.py | 105 ---------------------------- 1 file changed, 105 deletions(-) delete mode 100644 dotsandboxes/agents/algorithms/alphaBeta.py (limited to 'dotsandboxes/agents/algorithms/alphaBeta.py') diff --git a/dotsandboxes/agents/algorithms/alphaBeta.py b/dotsandboxes/agents/algorithms/alphaBeta.py deleted file mode 100644 index 8e041fe..0000000 --- a/dotsandboxes/agents/algorithms/alphaBeta.py +++ /dev/null @@ -1,105 +0,0 @@ -from GameState import GameState -class GameController(object): - def get_next_move(self, state): - # when you get a new move, it is assumed that the game is not ended yet - assert state.get_moves() - - -def alpha_beta(node, alpha, beta): - - # Based on https://en.wikipedia.org/wiki/Alpha%E2%80%93beta_pruning#Pseudocode - # node needs to support three operations: isTerminal(), value(), getChildren(), maximizingPlayer() - - if node.isTerminal(): - return node.value() - - if node.maximizingPlayer(): - - v = float("-inf") - for child in node.getChildren(): - - v = max(v, alpha_beta(child, alpha, beta)) - alpha = max(alpha, v) - if beta <= alpha: - break - - else: - - v = float("inf") - for child in node.getChildren(): - - v = min(v, alpha_beta(child, alpha, beta)) - beta = min(beta, v) - if beta <= alpha: - break - - return v - - -# A class for defining algorithms used (minimax and alpha-beta pruning) -class AlphaBeta: - - def miniMax(State, Ply_num): # Function for the minimax algorithm - - for i in range(State.Current.dimY): - for j in range(State.Current.dimX): - if State.Current.Mat[i][j] == ' ' and (j, i) not in State.children: - State.Make(j, i, True) - if Ply_num < 2: - return (i, j) - - Minimum_Score = 1000 - i = 0 - - j = 0 - for k, z in State.children.items(): - Result = Algo.Maximum(z, Ply_num - 1, Minimum_Score) - if Minimum_Score > Result: - Minimum_Score = Result - i = k[0] - j = k[1] - - return (i, j) - - # Alpha-beta pruning function for taking care of Alpha values - def Maximum(State, Ply_num, Alpha): - if Ply_num == 0: - return State.CurrentScore - - for i in range(State.Current.dimY): - for j in range(State.Current.dimX): - if State.Current.Mat[i][j] == ' ' and (j, i) not in State.children: - State.Make(j, i, False) - - Maximum_Score = -1000 - i = 0 - j = 0 - for k, z in State.children.items(): - Result = Algo.Minimum(z, Ply_num - 1, Maximum_Score) - if Maximum_Score < Result: - Maximum_Score = Result - if Result > Alpha: - return Result - - return Maximum_Score - - def Minimum(State, Ply_num, Beta): # Alpha-beta pruning function for taking care of Beta values - if Ply_num == 0: - return State.CurrentScore - - for i in range(State.Current.dimY): - for j in range(State.Current.dimX): - if State.Current.Mat[i][j] == ' ' and (j, i) not in State.children: - State.Make(j, i, True) - - Minimum_Score = 1000 - i = 0 - j = 0 - for k, z in State.children.items(): - Result = Algo.Maximum(z, Ply_num - 1, Minimum_Score) - if Minimum_Score > Result: - Minimum_Score = Result - if Result < Beta: - return Result - - return Minimum_Score -- cgit v1.2.3