def extract_plan(self, trail):
# The list of actions in a PredictiveImplicationLink. Sometimes there are none,
# sometimes one; if there is a SequentialAndLink then it can be more than one.
def actions(proofnode):
target = proofnode.op
if isinstance(target, rules.Rule):
return []
elif target.op == 'EvaluationLink':
tr = target.args[0]
if tr.op.name == 'agent_location':
def get_position(position_name):
return tuple(float(s[Var(i)].op.name) for i in [1,2,3])
pos_str = target.args[1].args[0].op.name
(x,y, _) = get_position(pos_str)
return [T('ExecutionLink', self.space.add('goto_obj'),
T('ListLink',
"%{x} %{y}" % locals()
)
)
]
else:
return []
#elif target.op in ['ExecutionLink', 'SequentialAndLink']:
# return [target]
elif rules.actionDone_template(self.space).unifies(target):
return target
else:
return []
# Extract all the targets in best-first order
proofnodes = trail.flatten()
proofnodes.reverse()
actions = concat_lists([actions(pn) for pn in proofnodes])
return actions
def recurse_app(self, app_pdn):
#print 'recurse_app', app_pdn
# You should try to produce every goal for an app.
# Let's say for simplicity, that you just expand one descendant
# of every goal (i.e. for every goal, you put in one step of effort)
# for proving it.
# If we've gone down to an axiom, give up. The axiom PDNs are added
# when an app is expanded by bc_step.
if len(app_pdn.op.goals) == 0:
return []
## If some of the goals have no children currently, let's assume it hasn't
## been expanded yet.
#if any(len(expr_pdn.args) == 0 for expr_pdn in app_pdn.args):
if app_pdn.bc_expanded == False:
app_pdn.bc_expanded = True
assert app_pdn.op in self.bc_later
return [app_pdn]
# Use a set because sometimes a goal will be used by more than one proof path.
return set(
concat_lists(
list(self.recurse_expr(expr_pdn))
for expr_pdn in app_pdn.args))
def extract_plan(self, trail):
# The list of actions in a PredictiveImplicationLink. Sometimes there are none,
# sometimes one; if there is a SequentialAndLink then it can be more than one.
def actions(proofnode):
target = proofnode.op
if isinstance(target, rules.Rule):
return []
elif target.op == 'EvaluationLink':
tr = target.args[0]
if tr.op.name == 'agent_location':
def get_position(position_name):
return tuple(
float(s[Var(i)].op.name) for i in [1, 2, 3])
pos_str = target.args[1].args[0].op.name
(x, y, _) = get_position(pos_str)
return [
T('ExecutionLink', self.space.add('goto_obj'),
T('ListLink', "%{x} %{y}" % locals()))
]
else:
return []
#elif target.op in ['ExecutionLink', 'SequentialAndLink']:
# return [target]
elif rules.actionDone_template(self.space).unifies(target):
return target
else:
return []
# Extract all the targets in best-first order
proofnodes = trail.flatten()
proofnodes.reverse()
actions = concat_lists([actions(pn) for pn in proofnodes])
return actions
def recurse_app(self, app_pdn):
#print 'recurse_app', app_pdn
# You should try to produce every goal for an app.
# Let's say for simplicity, that you just expand one descendant
# of every goal (i.e. for every goal, you put in one step of effort)
# for proving it.
# If we've gone down to an axiom, give up. The axiom PDNs are added
# when an app is expanded by bc_step.
if len(app_pdn.op.goals) == 0:
return []
## If some of the goals have no children currently, let's assume it hasn't
## been expanded yet.
#if any(len(expr_pdn.args) == 0 for expr_pdn in app_pdn.args):
if app_pdn.bc_expanded == False:
app_pdn.bc_expanded = True
assert app_pdn.op in self.bc_later
return [app_pdn]
# Use a set because sometimes a goal will be used by more than one proof path.
return set(concat_lists(list(self.recurse_expr(expr_pdn)) for expr_pdn in app_pdn.args))