def next_goal(self):
target_cell = None
dice = random.random()
if dice < self.cfg.effect.random_explo:
target_cell = random.sample(self.celltree.active_cells, 1)[0]
# elif dice < self.cfg.effect.random_explo + self.cfg.effect.unknown_explo:
# target_cell = self._priority_choice()
if target_cell is None:
target_cell = self._priority_choice()
if target_cell is None:
cell_uid = [cell.uid for cell in self.celltree.active_cells]
interests = [cell.interest() for cell in self.celltree.active_cells]
if sum(interests) > 0:
idx = toolbox.roulette_wheel(interests)
priority_uid = [cell.uid for cell in self.celltree.active_cells]
target_cell = self.celltree.cells[priority_uid[idx]]
if target_cell is not None:
return target_cell.random_point()
else:
return None
def next_goal(self):
target_cell = None
dice = random.random()
if dice < self.cfg.effect.random_explo:
target_cell = random.sample(self.celltree.active_cells, 1)[0]
# elif dice < self.cfg.effect.random_explo + self.cfg.effect.unknown_explo:
# target_cell = self._priority_choice()
if target_cell is None:
target_cell = self._priority_choice()
if target_cell is None:
cell_uid = [cell.uid for cell in self.celltree.active_cells]
interests = [
cell.interest() for cell in self.celltree.active_cells
]
if sum(interests) > 0:
idx = toolbox.roulette_wheel(interests)
priority_uid = [
cell.uid for cell in self.celltree.active_cells
]
target_cell = self.celltree.cells[priority_uid[idx]]
if target_cell is not None:
return target_cell.random_point()
else:
return None
def next_goal(self):
# choose an area proportionally to its interest
index = toolbox.roulette_wheel(
[cell.interest() for cell in self.cells])
# choose a random goal in it.
goal = self.cells[index].random_point()
return goal
def _compute_order_bias(self):
self.order_bias = []
weights_cpy = list(self.weights)
assert all(w > 0.0 for w in weights_cpy)
for _ in xrange(len(self.orders)):
idx = toolbox.roulette_wheel(weights_cpy)
weights_cpy[idx] = 0.0
self.order_bias.append(self.orders[idx])
def _compute_order_bias(self):
self.order_bias = []
weights_cpy = list(self.weights)
assert all(w > 0.0 for w in weights_cpy)
for _ in xrange(len(self.orders)):
idx = toolbox.roulette_wheel(weights_cpy)
weights_cpy[idx] = 0.0
self.order_bias.append(self.orders[idx])
def _priority_choice(self):
target_cell = None
priority_uid = [cell.uid for cell in self.celltree.active_cells]
priorities = [self._priority(cell) for cell in self.celltree.active_cells]
if sum(priorities) > 0:
idx = toolbox.roulette_wheel(priorities)
target_cell = self.celltree.cells[priority_uid[idx]]
return target_cell
def _priority_choice(self):
target_cell = None
priority_uid = [cell.uid for cell in self.celltree.active_cells]
priorities = [
self._priority(cell) for cell in self.celltree.active_cells
]
if sum(priorities) > 0:
idx = toolbox.roulette_wheel(priorities)
target_cell = self.celltree.cells[priority_uid[idx]]
return target_cell
def next_goal(self):
"""Generate a new goal"""
# decide between trying a virgin available cell
# or an interesting cell
dice = random.random()
if dice < self.cfg.effect.random_explo:
idx = random.randint(0, len(self.cells) - 1)
# elif dice < self.cfg.random_explo + self.cfg.unknown_explo:
# explo_interest = [cell.exploration_interest() for cell in self.cells]
# if sum(explo_interest) > 0:
# idx = toolbox.roulette_wheel(explo_interest)
# else:
# idx = toolbox.roulette_wheel([cell.interests[-1] for cell in self.cells])
else:
idx = toolbox.roulette_wheel([cell.interest() for cell in self.cells])
return self.cells[idx].random_point()
def next_goal(self):
"""Generate a new goal"""
# decide between trying a virgin available cell
# or an interesting cell
dice = random.random()
if dice < self.cfg.effect.random_explo:
idx = random.randint(0, len(self.cells) - 1)
# elif dice < self.cfg.random_explo + self.cfg.unknown_explo:
# explo_interest = [cell.exploration_interest() for cell in self.cells]
# if sum(explo_interest) > 0:
# idx = toolbox.roulette_wheel(explo_interest)
# else:
# idx = toolbox.roulette_wheel([cell.interests[-1] for cell in self.cells])
else:
idx = toolbox.roulette_wheel(
[cell.interest() for cell in self.cells])
return self.cells[idx].random_point()
def next_goal(self):
# choose an area proportionally to its interest
index = toolbox.roulette_wheel([cell.interest() for cell in self.cells])
# choose a random goal in it.
goal = self.cells[index].random_point()
return goal