def plan_cost(universe, plan):
if plan is None:
return INF
cost = universe.initial_cost
for action, args in plan:
instance = action.instantiate(args)
increases = get_increases(instance.effect)
# TODO - ensure that the last effect is used
new_cost = 0 # 0 | INF
if action.cost is not None:
new_cost += action.cost
for increase in increases:
if increase.function == TotalCost():
if isinstance(increase.value, Atom):
atom = increase.value
if atom in universe.perm_functions:
value = universe.evaluate_func(atom)
elif atom in universe.temp_functions:
value = universe.temp_functions[atom]
else:
raise ValueError(increase)
else:
value = increase.value
new_cost += value
#new_cost = min(new_cost, value)
#new_cost = max(new_cost, value)
#new_cost = value # TODO: several ways to handle repeated costs
cost += new_cost
return cost
def initial_pddl(self, costs):
atoms = list(self.get_initial_atoms())
if costs:
atoms.append(Initialize(TotalCost(), self.initial_cost))
return '(' + '\n\t'.join([':init'] +
sorted([atom.pddl() for atom in atoms])) + ')'
def plan_cost(universe, plan):
if plan is None:
return INF
cost = universe.initial_cost
for action, args in plan:
instance = action.instantiate(args)
increases = get_increases(instance.effect)
new_cost = 0
if action.cost is not None:
new_cost += action.cost
for increase in increases:
if increase.function == TotalCost():
if isinstance(increase.value, Atom):
if increase.value in universe.perm_functions:
value = universe.perm_functions[increase.value]
elif increase.value in universe.temp_functions:
value = universe.temp_functions[increase.value]
else:
raise ValueError(increase)
else:
value = increase.value
new_cost += value
cost += new_cost
return cost
def Cost(cost): # This is a shortcut
"""
Increase cost atom (increase total-cost F) which extends :class:`.Function` by
setting ``function`` to be :class:`.TotalCost()`.
:param cost: the numeric or :class:`.Function` amount that :class:`.TotalCost()` increases
"""
return Increase(TotalCost(), cost)
def problem_pddl(self, costs):
s = '(define (problem %s)\n' % self.problem_name
s += '(:domain %s)\n' % self.domain_name
#s += '(:objects' + self.constants_pddl() + ')\n' # NOTE - don't need this
s += self.initial_pddl(costs) + '\n'
s += self.goal_pddl() + '\n'
if costs:
s += '(:metric minimize %s)' % TotalCost().pddl()
return s + ')\n'
def problem_pddl(self, costs):
s = '(define (problem %s)\n' % self.problem_name
s += '(:domain %s)\n' % self.domain_name
s += self.initial_pddl(costs) + '\n'
s += self.goal_pddl() + '\n'
if costs:
s += '(:metric minimize %s)' % TotalCost().pddl()
return s + ')\n'
def __init__(self, cost):
"""
:param cost: the numeric or :class:`.Function` amount that :class:`.TotalCost()` increases
"""
super(Cost, self).__init__(TotalCost(), cost)
def initial_pddl(self, costs):
atoms = list(self.get_initial_atoms())
#atoms = list(apply_axioms(set(atoms), self.type_to_objects, instantiate_axioms(self)))
if costs: atoms.append(Initialize(TotalCost(), self.initial_cost))
return '(' + '\n\t'.join([':init'] +
sorted([atom.pddl() for atom in atoms])) + ')'