Ddedalus
diff --git a/‎Queens/Agents.py‎
Lines changed: 4 additions & 5 deletions b/‎Queens/Agents.py‎
Lines changed: 4 additions & 5 deletions
diff --git a/‎Queens/Environment.py‎
Lines changed: 3 additions & 1 deletion b/‎Queens/Environment.py‎
Lines changed: 3 additions & 1 deletion
diff --git a/‎Queens/main.py‎
Lines changed: 23 additions & 11 deletions b/‎Queens/main.py‎
Lines changed: 23 additions & 11 deletions
diff --git a/‎Queens/plots/08board06471352.png‎
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diff --git a/‎Queens/plots/08board14602753.png‎
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diff --git a/‎Queens/plots/08board17502463.png‎
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diff --git a/‎Queens/plots/08board24170635.png‎
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diff --git a/‎Queens/plots/08board37025164.png‎
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diff --git a/‎Queens/plots/08board37046152.png‎
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diff --git a/‎Queens/plots/08board41357206.png‎
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@@ -4,7 +4,6 @@
 def steepestAscentAgent():
 	state = yield "steepestAscentAgent"
 	while True:
-		# yield "Success", np.arange(0, 7, 1, dtype=int)
 		cols = count_collisions(state)
 		if cols == 0:
 			state = yield "Success", state
@@ -16,8 +15,8 @@ def steepestAscentAgent():
 				state = yield "NoOp", state
 
 
-def plateauExplorerGenerator():
-	state = yield "plateauExplorerGenerator"
+def plateauExplorerAgent():
+	state = yield "plateauExplorerAgent"
 	plateau = None
 	while True:
 		cols = count_collisions(state)
@@ -40,7 +39,7 @@ def plateauExplorerGenerator():
 				state = yield "NoOp", state
 
 
-def plateauLimitedGenerator(threshold):
+def plateauLimitedAgent(threshold):
 	state = yield "PlateauLimited, max={}".format(threshold)
 	plateau, count = None, 0
 	while True:
@@ -70,7 +69,7 @@ def plateauLimitedGenerator(threshold):
 				state = yield "NoOp", state
 
 
-def masterBeamGenerator(queens):
+def masterBeamAgent(queens):
 	tables = yield "Master Beam Generator"
 	k = len(tables)
 	while True:
 
@@ -16,6 +16,8 @@ def __init__(self, agents, queens=8, master=None):
 		self.tables = [Table(a, queens) for a in agents]
 		if master:
 			self.master = Table(master, queens)
+		else:
+			self.master = None
 		self.stats = StatsModule(agents, self.master)
 
 	def step(self):
@@ -49,7 +51,7 @@ def find_sol(self, how_many):
 		max_found = 0
 		while max_found < how_many:
 			self.step()
-			max_found = max(self.stats.solutions.values())
+			max_found = max(map(len, self.stats.solutions.values()))
 			progress_bar(max_found, how_many, "solutions found")
 		self.print_stats()
 
 
@@ -1,18 +1,30 @@
 from Queens.Environment import QueensEnv
 from Queens.Agents import *
 
-queens = 8  # how big is the
+queens = 8  # how big is the chessboard
 
-# plateauLimitedGenerator = PlateauLimitedAgent()
-# stepGenerator = SteepestAscentAgent()
-agents = [steepestAscentAgent() for t in range(4)]
-master = masterBeamGenerator(queens)
-env = QueensEnv(agents, master=master, queens=queens)
+env = QueensEnv([steepestAscentAgent()], queens=queens)
+env.run(200)
+# Let agent do 2000 steps and see how many solutions it finds
+
+print()
+steep = steepestAscentAgent()
+plateau = plateauExplorerAgent()
+env = QueensEnv([steep, plateau], queens=queens)
+env.find_sol(73)
+# challenge which agent finds 90% of all solutions possible
 
+print()
+agents = [plateauLimitedAgent(t) for t in range(6)]
+env = QueensEnv(agents, queens=queens)
+env.find_sol(73)
+# see for how long is it efficient to explore the plateau
 
-env.find_sol_master(82)
-# env.find_sol(10)
-# env.run(400)
-# env.print_stats()
-# print(env.stats.solutions)
+print()
+agents = [steepestAscentAgent() for t in range(4)]
+master = masterBeamAgent(queens)
+env = QueensEnv(agents, master=master, queens=queens)
+env.find_sol(73)
+# use beam search to find all the solutions
 
+# remember to check the plots ;)