def getSuccessors(self, state):
"""
For a given state, this should return a list of triples,
(successor, action, stepCost), where 'successor' is a
successor to the current state, 'action' is the action
required to get there, and 'stepCost' is the incremental
cost of expanding to that successor, 1 in our case.
You might want to this function:
For a list of propositions l and action a,
a.allPrecondsInList(l) returns true if the preconditions of a are in l
"""
self._expanded += 1
"*** YOUR CODE HERE ***"
# explain: Successors are the list of actions can be done from the current level
# I build the action lyer using pgNext.updateActionLayer
# then for each action I build a the Level that wholud have been created if only this action was selected
Successors = []
pg = state
previousPropositionLayer = pg.getPropositionLayer()
previousLayerPropositions = previousPropositionLayer.propositions
pgNext = PlanGraphLevel()
pgNext.updateActionLayer(previousPropositionLayer)
for Action in pgNext.actionLayer.actions:
if Action.isNoOp():
continue
pgNextAction = PlanGraphLevel()
pgNextAction.actionLayer.addAction(Action)
for prop in previousLayerPropositions:
pgNextAction.propositionLayer.addProposition(prop)
for prop in Action.getAdd():
new_prop = Proposition(prop.getName())
new_prop.addProducer(Action)
pgNextAction.propositionLayer.addProposition(new_prop)
for prop in Action.getDelete():
pgNextAction.propositionLayer.removePropositions(prop)
pgNextAction.updateMutexProposition()
Successors.append((pgNextAction, Action, 1))
return Successors
