def select_behavior(self):
try:
candidates = self.candidate_behaviors.pop()
except IndexError:
logdebug("No candidate behaviors received")
candidates = None
# Attempt to select a candidate behavior using a behavior network
if candidates is not None:
behavior = self.behavior_net.select_behavior(candidates, self.rate_in_hz)
if behavior is not None:
logdebug("Behavior selected: {}".format(behavior))
self.selected_behaviors.push(behavior)
def publish_selected_behavior(self):
# Check for available selected behaviors
try:
behavior = self.selected_behaviors.pop()
except IndexError:
behavior = None
# Publish selected behavior to selected behaviors queue for action
# execution (if applicable)
if behavior is not None:
logdebug("Publishing selected behaviors for execution")
SELECTED_BEHAVIORS_TOPIC.send(behavior)
else:
logdebug("No behaviors selected for execution")
def select_behavior(self, behaviors, rate_in_hz):
best_candidate = max(behaviors, key=attrgetter('activation'))
# [Behavior Selected]
if best_candidate.activation >= self.candidate_threshold:
logdebug("Behavior selected: {}".format(best_candidate))
# Remove activation from selected behavior
best_candidate.activation = 0.0
# Reset candidate threshold
self.candidate_threshold = self.initial_candidate_threshold
logdebug("Resetting candidate threshold to {}".format(self.candidate_threshold))
return best_candidate
# [No Selected Behavior]
else:
self.candidate_threshold \
= self.candidate_threshold_decay_strategy.get_next_value(self.candidate_threshold, rate_in_hz)
logdebug("No behavior selected. Reducing candidate_threshold to {}".format(self.candidate_threshold))
return None
def receive_coalitions(self):
logdebug("Receiving workspace coalitions")
def receive_cue(self):
logdebug("Receiving workspace cue")