def execute(self, agent, intention):
for _ in self.impl(agent, self.term, intention):
#fahid: log action
Logger.log_action(agent=agent.name.localpart,
payload={
"IDENTIFIER": self._get_readable_name(),
"CODE_LINE": self.loc.lineno,
"CODE_FILE": self.loc.filename
},
bb_payload=agent.get_belief_base())
yield
def _on_run(self):
Logger.log_action(
agent=self.agent.name,
payload={
"META": "Running Behaviour",
"IDENTIFIER": self.name,
"CODE_LINE": "",
"CODE_FILE": ""
},
bb_payload=[]
)
def call(self, trigger, goal_type, term, calling_intention, delayed=False):
# Modify beliefs.
if goal_type == agentspeak.GoalType.belief:
if trigger == agentspeak.Trigger.addition:
self.add_belief(term, calling_intention.scope)
else:
found = self.remove_belief(term, calling_intention)
if not found:
return True
# Freeze with caller scope.
frozen = agentspeak.freeze(term, calling_intention.scope, {})
if not isinstance(frozen, agentspeak.Literal):
raise AslError("expected literal")
# Wake up waiting intentions.
for intention_stack in self.intentions:
if not intention_stack:
continue
intention = intention_stack[-1]
if not intention.waiter or not intention.waiter.event:
continue
event = intention.waiter.event
if event.trigger != trigger or event.goal_type != goal_type:
continue
if agentspeak.unifies_annotated(event.head, frozen):
intention.waiter = None
# fahid..... log plan trace here.....
self.get_belief_base()
applicable_plans = self.plans[(trigger, goal_type, frozen.functor,
len(frozen.args))]
applicable_plans_trace = []
for plan in applicable_plans:
"""
if type(plan.context) is list:
print (">>>> list")
else:
print (">>>>> ", type(plan.context))
if type(plan.context) is AndQuery:
print(".....")
print(plan.context.left)
print(plan.context.right)
elif type(plan.context) is OrQuery:
print("////")
print(plan.context.left)
print(plan.context.right)
"""
applicable_plans_trace.append({
"IDENTIFIER":
str(plan.head),
"CONTEXT":
flatten_context(
plan.context
), #str(plan.context) if type(plan.context) is not type (NotQuery("")) else "not " + str(plan.context.query),
"CODE_LINE":
"",
"CODE_FILE":
""
})
if len(applicable_plans_trace) > 0:
Logger.log_plan_trace(agent=self.name,
payload=applicable_plans_trace,
bb_payload=self.get_belief_base())
choicepoint = object()
intention = Intention()
# Find matching plan.
counter = -1
for plan in applicable_plans:
counter += 1
for _ in agentspeak.unify_annotated(plan.head, frozen,
intention.scope,
intention.stack):
for _ in plan.context.execute(self, intention):
intention.head_term = frozen
intention.instr = plan.body
intention.calling_term = term
if not delayed and self.intentions:
for intention_stack in self.intentions:
if intention_stack[-1] == calling_intention:
intention_stack.append(intention)
# Fahid: log selected plan....
Logger.log_plan_selection(
agent=self.name,
payload=applicable_plans_trace[counter],
bb_payload=self.get_belief_base())
return True
new_intention_stack = collections.deque()
new_intention_stack.append(intention)
self.intentions.append(new_intention_stack)
# Fahid: Log selected plan.....
Logger.log_plan_selection(
agent=self.name,
payload=applicable_plans_trace[counter],
bb_payload=self.get_belief_base())
return True
#fahid: log not found...
if goal_type == agentspeak.GoalType.achievement:
raise AslError("no applicable plan for %s%s%s/%d" %
(trigger.value, goal_type.value, frozen.functor,
len(frozen.args)))
elif goal_type == agentspeak.GoalType.test:
return self.test_belief(term, calling_intention)
return True
def add_behaviour(self, behaviour, template=None):
super().add_behaviour(behaviour, template)
Logger.add_persistent_data(self.name, {"source": "self", "type": "Behaviour", "value": behaviour.get_name()} )
def remove_behaviour(self, behaviour):
super().remove_behaviour(behaviour)
Logger.remove_persistent_data(self.name, {"source": "self", "type": "Behaviour", "value": behaviour.get_name()})
def on_resume(self, owner):
Logger.add_persistent_data(self.agent.name, {"source": "self", "type": "Behaviour", "value": self.name} )
def on_pause(self, owner):
Logger.remove_persistent_data(owner, {"source": "self", "type": "Behaviour", "value": self.name} )
def _on_end(self):
Logger.remove_persistent_data(self.agent.name, {"source": "self", "type": "Behaviour", "value": self.name} )
def _on_start(self):
Logger.add_persistent_data(self.agent.name, {"source": "self", "type": "Behaviour", "value": self.name} )