def next_action(self):
"""Return the next action this agent wants to perform.
:return: (row, column, orientation)
"""
start_time = time.time()
free_lines = self.board.get_potential_moves()
if len(free_lines) == 0:
# Board full
return None
signal.alarm(self.timelimit)
try:
(s, value) = self.tree.get_best_move_for_set(self.moves.copy())
if not isinstance(s, str) or self.mcts == False or s in self.moves:
(a, b) = heuristics.find_good_move(self.board)
signal.alarm(0)
self.mcts = False
if a % 2 == 0:
o = "h"
c = b
r = int(a / 2)
else:
o = "v"
c = b
r = self.odds.index(a)
self.heuristicmoves += 1
elapsed_time = time.time() - start_time
self.times_for_move.append(elapsed_time)
return r, c, o
else:
signal.alarm(0)
self.mctsmoves += 1
r, c, o = s.split(",")
elapsed_time = time.time() - start_time
self.times_for_move.append(elapsed_time)
return r, c, o
except TimeoutException:
(a, b) = heuristics.find_good_move(self.board)
signal.alarm(0)
self.mcts = False
if a % 2 == 0:
o = "h"
c = b
r = int(a / 2)
else:
o = "v"
c = b
r = self.odds.index(a)
self.heuristicmoves += 1
elapsed_time = time.time() - start_time
self.times_for_move.append(elapsed_time)
return r, c, o
def next_action(self):
"""Return the next action this agent wants to perform.
:return: (row, column, orientation)
"""
free_lines = self.board.get_potential_moves()
if len(free_lines) == 0:
# Board full
return None
(s, value) = self.tree.get_best_move_for_set(self.moves.copy())
if not isinstance(s, str) or self.mcts == False or s in self.moves:
(a, b) = heuristics.find_good_move(self.board)
self.mcts = False
if a % 2 == 0:
o = "h"
c = b
r = int(a / 2)
else:
o = "v"
c = b
r = self.odds.index(a)
self.heuristicmoves += 1
return r, c, o
else:
self.mctsmoves += 1
r, c, o = s.split(",")
return r, c, o
def next_action(self):
"""Return the next action this agent wants to perform.
:return: (row, column, orientation)
"""
free_lines = self.board.get_potential_moves()
if len(free_lines) == 0:
# Board full
return None
move = False
if self.mcts:
value = 0
for l in it.permutations(self.moves, len(self.moves)):
go = True
for seq in self.shouldnotstartwith:
li = list(l)
if li[:len(seq)] == seq:
go = False
break
if go:
(newmove,rate) = self.tree.get_best_move_for_set(list(l).copy())
if rate > value and newmove not in self.moves:
value = rate
move = newmove
self.mctsmoves += 1
r,c,o = move.split(",")
return r,c,o
else:
self.shouldnotstartwith.append(list(l))
print("SHOULDNTO",self.shouldnotstartwith)
print("MCTS POWER")
if not isinstance(move, str) or self.mcts == False:
(a,b) = heuristics.find_good_move(self.board)
self.mcts = False
if a%2==0:
o = "h"
c = b
r = int(a/2)
else:
o = "v"
c = b
r = self.odds.index(a)
self.heuristicmoves += 1
return r, c, o
def next_action(self):
"""Return the next action this agent wants to perform.
:return: (row, column, orientation)
"""
start_time = time.time()
free_lines = self.board.get_potential_moves()
if len(free_lines) == 0:
# Board full
return None
(a, b) = heuristics.find_good_move(self.board)
if a % 2 == 0:
o = "h"
c = b
r = int(a / 2)
else:
o = "v"
c = b
r = self.odds.index(a)
elapsed_time = time.time() - start_time
self.times_for_move.append(elapsed_time)
return r, c, o