def add_stream_costs(node_from_atom, instantiated, unit_efforts, effort_weight):
# TODO: instantiate axioms with negative on effects for blocking
# TODO: fluent streams using conditional effects. Special fluent predicate for inputs to constraint
# This strategy will only work for relaxed to ensure that the current state is applied
for instance in instantiated.actions:
# TODO: prune stream actions here?
# Ignores conditional effect costs
facts = []
for precondition in get_literals(instance.action.precondition):
if precondition.negated:
continue
args = [instance.var_mapping.get(arg, arg) for arg in precondition.args]
literal = precondition.__class__(precondition.predicate, args)
fact = fact_from_fd(literal)
if fact in node_from_atom:
facts.append(fact)
#effort = COMBINE_OP([0] + [node_from_atom[fact].effort for fact in facts])
stream_plan = []
extract_stream_plan(node_from_atom, facts, stream_plan)
if unit_efforts:
effort = len(stream_plan)
else:
effort = scale_cost(sum([0] + [r.instance.get_effort() for r in stream_plan]))
if effort_weight is not None:
instance.cost += effort_weight*effort
# TODO: bug! The FD instantiator prunes the result.external.stream_fact
for result in stream_plan:
# TODO: need to make multiple versions if several ways of achieving the action
if is_optimizer_result(result):
fact = substitute_expression(result.external.stream_fact, result.get_mapping())
atom = fd_from_fact(fact)
instantiated.atoms.add(atom)
effect = (tuple(), atom)
instance.add_effects.append(effect)
def add_stream_efforts(node_from_atom, instantiated, effort_weight, **kwargs):
if effort_weight is None:
return
# TODO: make effort just a multiplier (or relative) to avoid worrying about the scale
# TODO: regularize & normalize across the problem?
#efforts = []
for instance in instantiated.actions:
# TODO: prune stream actions here?
# TODO: round each effort individually to penalize multiple streams
facts = get_instance_facts(instance, node_from_atom)
#effort = COMBINE_OP([0] + [node_from_atom[fact].effort for fact in facts])
stream_plan = []
extract_stream_plan(node_from_atom, facts, stream_plan)
effort = compute_plan_effort(stream_plan, **kwargs)
instance.cost += scale_cost(effort_weight * effort)
