def parse_effect(alist, type_dict, predicate_dict):
tag = alist[0]
if tag == "and":
return pddl.ConjunctiveEffect([
parse_effect(eff, type_dict, predicate_dict) for eff in alist[1:]
])
elif tag == "forall":
assert len(alist) == 3
parameters = parse_typed_list(alist[1])
effect = parse_effect(alist[2], type_dict, predicate_dict)
return pddl.UniversalEffect(parameters, effect)
elif tag == "when":
assert len(alist) == 3
condition = parse_condition(alist[1], type_dict, predicate_dict)
effect = parse_effect(alist[2], type_dict, predicate_dict)
return pddl.ConditionalEffect(condition, effect)
elif tag == "increase":
assert len(alist) == 3
assert alist[1] == ['total-cost']
assignment = parse_assignment(alist)
return pddl.CostEffect(assignment)
else:
# We pass in {} instead of type_dict here because types must
# be static predicates, so cannot be the target of an effect.
return pddl.SimpleEffect(parse_literal(alist, {}, predicate_dict))
def parse_effect(alist, type_dict, predicate_dict):
tag = alist[0]
if tag == "and":
return [
pddl.ConjunctiveEffect(conjuncts)
for conjuncts in cartesian_product(*[
parse_effect(eff, type_dict, predicate_dict)
for eff in alist[1:]
])
]
elif tag == "forall":
assert len(alist) == 3
parameters = parse_typed_list(alist[1])
effects = parse_effect(alist[2], type_dict, predicate_dict)
assert 1 == len(effects), \
"Error: Cannot embed non-determinism inside of a forall (for now)."
return [pddl.UniversalEffect(parameters, effect) for effect in effects]
elif tag == "when":
assert len(alist) == 3
condition = parse_condition(alist[1], type_dict, predicate_dict)
effects = parse_effect(alist[2], type_dict, predicate_dict)
assert all([eff.probability == 1 for eff in effects]), \
"Error: (probabilistic ...) within (when ...) is currently not supported"
return [
pddl.ConditionalEffect(condition, effect) for effect in effects
]
elif tag == "increase":
assert len(alist) == 3
assert alist[1] == ['total-cost']
assignment = parse_assignment(alist)
return [pddl.CostEffect(assignment)]
elif tag == "probabilistic":
# Generate effects for each outcome and then set their probability appropriately
assert (len(alist)-1) % 2 == 0,\
"Each probabilistic outcome must have an associated probability"
outcome_pairs = [(alist[i], alist[i + 1])
for i in range(1, len(alist), 2)]
remaining_probability = fractions.Fraction(1)
outcomes = []
for pair in outcome_pairs:
effects = parse_effect(pair[1], type_dict, predicate_dict)
for eff in effects:
# Apply the base probability in the pair to this individual effect
eff.probability *= fractions.Fraction(
pair[0]).limit_denominator()
remaining_probability -= eff.probability
outcomes.append(eff)
remaining_probability = remaining_probability.limit_denominator()
if (remaining_probability > 0):
remaining_eff = pddl.SimpleEffect(None)
remaining_eff.probability = remaining_probability
outcomes.append(remaining_eff)
return outcomes
else:
# We pass in {} instead of type_dict here because types must
# be static predicates, so cannot be the target of an effect.
return [pddl.SimpleEffect(parse_literal(alist, {}, predicate_dict))]