Add debug configs,

7 files changed, 164 insertions, 41 deletions

diff --git a/python/MCTS.py b/python/MCTS.py
index a65e2d4..6c71ba9 100644
--- a/python/MCTS.py
+++ b/python/MCTS.py
@@ -1,6 +1,6 @@
 import math
 from copy import deepcopy
-from time import clock
+from time import perf_counter
 from random import choice
 
 from GameState import GameState
@@ -135,8 +135,8 @@ class MCTSGameController(GameController):
         self.root_node = MCTSNode(state)
         iterations = 0
 
-        start_time = clock()
-        while clock() < start_time + time_allowed:
+        start_time = perf_counter()
+        while perf_counter() < start_time + time_allowed:
             node = self.select()
 
             if node.pending_moves != set():
diff --git a/python/agent_AB.py b/python/agent_AB.py
new file mode 100644
index 0000000..4b1ace1
--- /dev/null
+++ b/python/agent_AB.py
@@ -0,0 +1,57 @@
+import dotsandboxes.dotsandboxesagent as dba
+
+import sys
+import argparse
+import logging
+from GameState import GameState, DotsAndBoxesState
+from MCTS import MCTSNode, MCTSGameController
+import alphaBeta
+
+
+logger = logging.getLogger(__name__)
+games = {}
+agentclass = dba
+
+
+class Agent(dba.DotsAndBoxesAgent):
+    def __init__(self, player, nb_rows, nb_cols, timelimit):
+        super(Agent, self).__init__(player, nb_rows, nb_cols, timelimit)
+        self.GameStateClass = DotsAndBoxesState
+        self.game_state = self.GameStateClass(nb_rows, nb_cols, player)
+        # self.controller = controller
+
+    def register_action(self, row, column, orientation, player):
+        super(Agent, self).register_action(row, column, orientation, player)
+        # adjust agent specific board representation
+        move = (row, column, orientation)
+        self.game_state.play_move(move)
+
+    def next_action(self):
+        r, c, o = self.controller.get_next_move(self.game_state, time_allowed=self.timelimit)
+        return r, c, o
+
+    def end_game(self):
+        super(Agent, self).end_game()
+
+
+# Adapted from provided code
+def main(argv=None):
+    global agentclass
+    parser = argparse.ArgumentParser(description='Start agent to play Dots and Boxes')
+    parser.add_argument('--verbose', '-v', action='count', default=0, help='Verbose output')
+    parser.add_argument('--quiet', '-q', action='count', default=0, help='Quiet output')
+    parser.add_argument('port', metavar='PORT', type=int, help='Port to use for server')
+    args = parser.parse_args(argv)
+    print(args)
+
+    logger.setLevel(max(logging.INFO - 10 * (args.verbose - args.quiet), logging.DEBUG))
+    logger.addHandler(logging.StreamHandler(sys.stdout))
+
+    agentclass = Agent
+    dba.agentclass = Agent
+    dba.start_server(args.port)
+
+
+if __name__ == "__main__":
+    sys.exit(main())
+
diff --git a/python/agent.py b/python/agent_MCTS.py
index 49bc1cc..b0072cf 100644
--- a/python/agent.py
+++ b/python/agent_MCTS.py
@@ -5,11 +5,12 @@ import argparse
 import logging
 from GameState import GameState, DotsAndBoxesState
 from MCTS import MCTSNode, MCTSGameController
+import alphaBeta
 
 
 logger = logging.getLogger(__name__)
 games = {}
-agentclass = None
+agentclass = dba
 
 
 class Agent(dba.DotsAndBoxesAgent):
@@ -41,6 +42,7 @@ def main(argv=None):
     parser.add_argument('--quiet', '-q', action='count', default=0, help='Quiet output')
     parser.add_argument('port', metavar='PORT', type=int, help='Port to use for server')
     args = parser.parse_args(argv)
+    print(args)
 
     logger.setLevel(max(logging.INFO - 10 * (args.verbose - args.quiet), logging.DEBUG))
     logger.addHandler(logging.StreamHandler(sys.stdout))
diff --git a/python/alphaBeta.py b/python/alphaBeta.py
index 01f82cf..31fa578 100644
--- a/python/alphaBeta.py
+++ b/python/alphaBeta.py
@@ -1,30 +1,99 @@
 
 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
+
+    # 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
diff --git a/python/dotsandboxes/dotsandboxesagent.py b/python/dotsandboxes/dotsandboxesagent.py
index c8bc05e..9fe6cb8 100644
--- a/python/dotsandboxes/dotsandboxesagent.py
+++ b/python/dotsandboxes/dotsandboxesagent.py
@@ -15,8 +15,6 @@ import asyncio
 import websockets
 import json
 from collections import defaultdict
-import random
-
 
 logger = logging.getLogger(__name__)
 games = {}
diff --git a/python/dotsandboxes/static/dotsandboxes.html b/python/dotsandboxes/static/dotsandboxes.html
index ecbcbb4..4e97508 100644
--- a/python/dotsandboxes/static/dotsandboxes.html
+++ b/python/dotsandboxes/static/dotsandboxes.html
@@ -2,9 +2,6 @@
 <html>
 <html lang="en">
 <meta charset="utf-8">
-<meta name="author" content="Wannes Meert">
-<meta name="description" content="Dots-and-Boxes game. Part of the Machine Learning: Project course at KU Leuven (Hendrik Blockeel, Wannes Meert).">
-<meta name="keywords" content="artificial intelligence,AI,machine learning,dots and boxes,KU Leuven">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <title>Dots and Boxes</title>
 <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/css/bootstrap.min.css" integrity="sha384-Gn5384xqQ1aoWXA+058RXPxPg6fy4IWvTNh0E263XmFcJlSAwiGgFAW/dAiS6JXm" crossorigin="anonymous">
@@ -45,9 +42,6 @@
 				</div>
 			</div>
 		</div>
-		<div class="footer">
-		<small>&copy; <a href="https://dtai.cs.kuleuven.be">DTAI Research Group</a>, KU Leuven &mdash; <a href="https://github.com/wannesm/dotsandboxes">Source</a></small>
-		</div>
 	</div>
 	<script src="https://d3js.org/d3.v4.min.js"></script>
 	<script src="dotsandboxes.js"></script>
diff --git a/python/start.sh b/python/start.sh
index 6be69a2..455944d 100755
--- a/python/start.sh
+++ b/python/start.sh
@@ -1,7 +1,10 @@
+#/bin/bash
 (cd dotsandboxes; python3 dotsandboxesserver.py 8080) &
 python3 agent.py 10001 &
 python3 agent.py 10002 &
-read -p "Press enter to close all programs."
+
+echo "Press enter to close all programs"
+read TRASH;
 
 trap "exit" INT TERM
 trap "kill 0" EXIT