def __init__(self, problem, state, serialize=True, ignore_mutexes=False):
"""
Parameters
----------
problem : PlanningProblem
An instance of the PlanningProblem class
state : tuple(bool)
An ordered sequence of True/False values indicating the literal value
of the corresponding fluent in problem.state_map
serialize : bool
Flag indicating whether to serialize non-persistence actions. Actions
should NOT be serialized for regression search (e.g., GraphPlan), and
_should_ be serialized if the planning graph is being used to estimate
a heuristic
"""
self._serialize = serialize
self._is_leveled = False
self._ignore_mutexes = ignore_mutexes
self.goal = set(problem.goal)
# make no-op actions that persist every literal to the next layer
no_ops = [
make_node(n, no_op=True)
for n in chain(*(makeNoOp(s) for s in problem.state_map))
]
self._actionNodes = no_ops + [
make_node(a) for a in problem.actions_list
]
# initialize the planning graph by finding the literals that are in the
# first layer and finding the actions they they should be connected to
literals = [s if f else ~s for f, s in zip(state, problem.state_map)]
layer = LiteralLayer(literals, ActionLayer(), self._ignore_mutexes)
layer.update_mutexes()
self.literal_layers = [layer]
self.action_layers = []
def setUp(self):
self.cake_problem = have_cake()
self.cake_pg = PlanningGraph(self.cake_problem,
self.cake_problem.initial,
serialize=False).fill()
eat_action, bake_action = [
a for a in self.cake_pg._actionNodes if not a.no_op
]
no_ops = [a for a in self.cake_pg._actionNodes if a.no_op]
# bake has the effect Have(Cake) which is the logical negation of the effect
# ~Have(cake) from the persistence action ~NoOp::Have(cake)
self.inconsistent_effects_actions = [bake_action, no_ops[3]]
# the persistence action ~NoOp::Have(cake) has the effect ~Have(cake), which is
# the logical negation of Have(cake) -- the precondition for the Eat(cake) action
self.interference_actions = [eat_action, no_ops[3]]
# eat has precondition Have(cake) and bake has precondition ~Have(cake)
# which are logical inverses, so eat & bake should be mutex at every
# level of the planning graph where both actions appear
self.competing_needs_actions = [eat_action, bake_action]
self.ac_problem = air_cargo_p1()
self.ac_pg_serial = PlanningGraph(self.ac_problem,
self.ac_problem.initial).fill()
# In(C1, P2) and In(C2, P1) have inconsistent support when they first appear in
# the air cargo problem,
self.inconsistent_support_literals = [
expr("In(C1, P2)"), expr("In(C2, P1)")
]
# some independent nodes for testing mutexes
at_here = expr('At(here)')
at_there = expr('At(there)')
self.pos_literals = [at_here, at_there]
self.neg_literals = [~x for x in self.pos_literals]
self.literal_layer = LiteralLayer(
self.pos_literals + self.neg_literals, ActionLayer())
self.literal_layer.update_mutexes()
# independent actions for testing mutex
self.actions = [
make_node(
Action(expr('Go(here)'), [set(), set()],
[set([at_here]), set()])),
make_node(
Action(expr('Go(there)'), [set(), set()],
[set([at_there]), set()]))
]
self.no_ops = [
make_node(x)
for x in chain(*(makeNoOp(l) for l in self.pos_literals))
]
self.action_layer = ActionLayer(self.no_ops + self.actions,
self.literal_layer)
self.action_layer.update_mutexes()
for action in self.no_ops + self.actions:
self.action_layer.add_inbound_edges(action, action.preconditions)
self.action_layer.add_outbound_edges(action, action.effects)
# competing needs tests -- build two copies of the planning graph: one where
# A, B, and C are pairwise mutex, and another where they are not
A, B, C = expr('A'), expr('B'), expr('C')
self.fake_competing_needs_actions = [
make_node(
Action(expr('FakeAction(A)'), [set([A]), set()],
[set([A]), set()])),
make_node(
Action(expr('FakeAction(B)'), [set([B]), set()],
[set([B]), set()])),
make_node(
Action(expr('FakeAction(C)'), [set([C]), set()],
[set([C]), set()]))
]
competing_layer = LiteralLayer([A, B, C], ActionLayer())
for a1, a2 in combinations([A, B, C], 2):
competing_layer.set_mutex(a1, a2)
self.competing_action_layer = ActionLayer(competing_layer.parent_layer,
competing_layer, False, True)
for action in self.fake_competing_needs_actions:
self.competing_action_layer.add(action)
competing_layer |= action.effects
competing_layer.add_outbound_edges(action, action.preconditions)
self.competing_action_layer.add_inbound_edges(
action, action.preconditions)
self.competing_action_layer.add_outbound_edges(
action, action.effects)
not_competing_layer = LiteralLayer([A, B, C], ActionLayer())
self.not_competing_action_layer = ActionLayer(
not_competing_layer.parent_layer, not_competing_layer, False, True)
for action in self.fake_competing_needs_actions:
self.not_competing_action_layer.add(action)
not_competing_layer |= action.effects
not_competing_layer.add_outbound_edges(action,
action.preconditions)
self.not_competing_action_layer.add_inbound_edges(
action, action.preconditions)
self.not_competing_action_layer.add_outbound_edges(
action, action.effects)