def _abolish(agent, term, intention):
memo = {}
pattern = agentspeak.freeze(term.args[0], intention.scope, memo)
group = agent.beliefs[pattern.literal_group()]
for old_belief in list(group):
if agentspeak.unifies_annotated(old_belief, pattern):
group.remove(old_belief)
yield
def test_unifies_annotated(self):
X = agentspeak.Var()
Y = agentspeak.Var()
foo_a = agentspeak.Literal("foo", (), ("a", ))
foo_ab = agentspeak.Literal("foo", (), ("a", "b"))
foo_XY = agentspeak.Literal("foo", (), (X, Y))
foo_XX = agentspeak.Literal("foo", (), (X, X))
self.assertTrue(agentspeak.unifies_annotated(foo_a, foo_ab))
self.assertTrue(agentspeak.unifies_annotated(foo_a, foo_XY))
self.assertTrue(agentspeak.unifies_annotated(foo_a, foo_XX))
self.assertTrue(agentspeak.unifies_annotated(foo_ab, foo_XY))
self.assertTrue(agentspeak.unifies_annotated(foo_XY, foo_ab))
self.assertTrue(agentspeak.unifies_annotated(foo_XX, foo_ab))
self.assertTrue(agentspeak.unifies_annotated(foo_XX, foo_ab))
self.assertFalse(agentspeak.unifies_annotated(foo_ab, foo_XX))
self.assertFalse(agentspeak.unifies_annotated(foo_XY, foo_a))
def test_unifies_annotated():
X = agentspeak.Var()
Y = agentspeak.Var()
foo_a = agentspeak.Literal("foo", (), ("a",))
foo_ab = agentspeak.Literal("foo", (), ("a", "b"))
foo_XY = agentspeak.Literal("foo", (), (X, Y))
foo_XX = agentspeak.Literal("foo", (), (X, X))
assert agentspeak.unifies_annotated(foo_a, foo_ab)
assert agentspeak.unifies_annotated(foo_a, foo_XY)
assert agentspeak.unifies_annotated(foo_a, foo_XX)
assert agentspeak.unifies_annotated(foo_ab, foo_XY)
assert agentspeak.unifies_annotated(foo_XY, foo_ab)
assert agentspeak.unifies_annotated(foo_XX, foo_ab)
assert agentspeak.unifies_annotated(foo_XX, foo_ab)
assert not agentspeak.unifies_annotated(foo_ab, foo_XX)
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 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
applicable_plans = self.plans[(trigger, goal_type, frozen.functor,
len(frozen.args))]
choicepoint = object()
intention = Intention()
# Find matching plan.
for plan in applicable_plans:
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)
return True
new_intention_stack = collections.deque()
new_intention_stack.append(intention)
self.intentions.append(new_intention_stack)
return True
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