def preprocess(self):
# Project the initial state
new_init = PDKB(self.init.depth, self.init.agents, self.init.props)
rmls = self.init.rmls
for ag in self.agent_projection:
rmls = project(rmls, ag)
new_init.rmls = rmls
self.init = new_init
self.orig_cond_count = 0
self.comp_cond_count = 0
# Expand and project the action's effects with derived conditional effects
for act in self.domain.actions:
self.orig_cond_count += sum([
len(act.effs[i][0]) + len(act.effs[i][1])
for i in range(len(act.effs))
])
act.expand()
self.comp_cond_count += sum([
len(act.effs[i][0]) + len(act.effs[i][1])
for i in range(len(act.effs))
])
for ag in self.agent_projection:
act.project_effects(ag)
if self.agent_projection:
# We project the precondition separately since we are in the
# perspective of the final agent
act.project_pre(self.agent_projection[-1])
def pddl(self):
pdkb = PDKB(self.depth, self.agents, self.props)
akpdkb = PDKB(0, [], self.akprops)
to_ret = "(define (domain %s)\n\n" % self.name
to_ret += " (:requirements :strips :conditional-effects)\n\n"
to_ret += " (:predicates\n"
PROPS = pdkb.all_rmls | akpdkb.all_rmls
assert 0 == len(
pdkb.all_rmls & akpdkb.all_rmls
), "Error: Detected overlap in regular fluents and always known fluents"
print("\n\n# Agents: %d" % len(self.agents))
print("# Props: %d" % len(PROPS))
print("# Acts: %d" % len(self.actions))
print("# Effs: %d" % sum([a.num_effs() for a in self.actions]))
print("Depth: %d" % self.depth)
for (key, rml) in sorted([(str(r), r) for r in PROPS]):
to_ret += " (%s)\n" % rml.pddl()
to_ret += " )\n\n"
for (key, act) in sorted([(a.name, a) for a in self.actions]):
to_ret += "%s\n\n" % act.pddl()
to_ret += ')'
return to_ret
def __init__(self,
name,
depth,
agents,
props,
akprops,
derived_cond,
extra_ancillary=[]):
self.name = name
self.depth = depth
self.agents = agents
self.props = props
self.akprops = akprops
self.derived_cond = derived_cond
self.pre = PDKB(depth, agents, props)
self.npre = PDKB(depth, agents, props)
self.effs = []
# Detect all of the ancillary effects
self.COMPILERS_POS = []
self.COMPILERS_NEG = []
for mod_name in ancillary.compute_modules() + extra_ancillary:
mod = importlib.import_module(mod_name)
self.COMPILERS_POS.extend(mod.COMPILERS_POS)
self.COMPILERS_NEG.extend(mod.COMPILERS_NEG)
def random_pdkb(depth, numAg, fluents, numRMLs, output=True):
agents = list(range(1, numAg + 1))
kb = PDKB(depth, agents, fluents)
count = 0
new_rmls = set()
while count < numRMLs:
rml = random_rml(depth, agents, fluents)
if rml not in kb.rmls and neg(rml) not in kb.rmls:
# Take advantage of the fact that we know the closure
# is just the union of the closure of each RML
test_rmls = list(kd_closure(rml)) + [rml]
cons = True
for trml in test_rmls:
if neg(trml) in kb.rmls:
cons = False
if cons:
if output:
print "Added %s" % rml
for trml in test_rmls:
kb.add_rml(trml)
new_rmls.add(rml)
count += 1
kb.rmls = new_rmls
return kb
def project(self, ag, akprops):
condp = PDKB(self.condp.depth, self.condp.agents, self.condp.props)
condn = PDKB(self.condp.depth, self.condp.agents, self.condp.props)
for rml in self.condp:
if isinstance(rml, Possible):
condn.add_rml(neg(rml.rml))
elif isinstance(rml, Belief):
condp.add_rml(rml.rml)
elif rml.is_ak(akprops):
condp.add_rml(rml)
else:
assert False, "Trying to project a Literal?"
if isinstance(self.eff, Possible):
return (False,
CondEff(condp, condn, neg(self.eff.rml), self.ma_cond,
self.reason))
elif isinstance(self.eff, Belief):
return (True,
CondEff(condp, condn, self.eff.rml, self.ma_cond,
self.reason))
elif self.eff.is_ak(akprops):
return (True,
CondEff(condp, condn, self.eff, self.ma_cond, self.reason))
else:
assert False, "Bad effect for projection?"
def parse_goal(self, prob):
self.goal = PDKB(self.domain.depth, self.domain.agents,
self.domain.props)
assert isinstance(prob.goal, pdkb.pddl.formula.And)
for g in prob.goal.args:
self.goal.add_rml(prim2rml(g))
def test3():
kb = PDKB(1, [1], map(Literal, ['p', 'q']))
l1 = Literal('p')
l2 = Belief(1, Literal('q'))
kb.add_rml(l1)
kb.add_rml(l2)
test_kripke(kb, [l1, l2])
def test5():
kb = PDKB(2, [1,2], map(Literal, ['p', 'q']))
rmls = [
Literal('p'),
Belief(1, Literal('q')),
Belief(1, Belief(2, neg(Literal('q'))))
]
for rml in rmls:
kb.add_rml(rml)
test_kripke(kb, rmls)
def convert_action(action, depth, agents, props, akprops):
if str(action.dcond) == '(always)':
act = Action(action.name, depth, agents, props, akprops, True)
elif str(action.dcond) == '(never)':
act = Action(action.name, depth, agents, props, akprops, False)
elif action.dcond:
act = Action(action.name, depth, agents, props, akprops,
parse_ma_cond(action.dcond))
else:
assert False, "Error for action %s. You need to specify the type of derived condition ('always', 'never', or 'custom')." % action.name
assert isinstance(action.precondition, pdkb.pddl.formula.And)
for pre in action.precondition.args:
act.add_pre(prim2rml(pre),
negate=isinstance(pre, pdkb.pddl.formula.Not))
def get_arg_list(form, objtype):
if isinstance(form, objtype):
return form.args
else:
return [form]
#print dir(action)
#['dcond', 'dump', 'effect', 'export', 'is_equal', 'name', 'observe', 'parameters', 'precondition']
#['agent_list', 'args', 'dump', 'enforce_normalize', 'export', 'is_equal', 'name', 'normalize', 'predicate', 'to_ground']
for nondet_eff in get_arg_list(action.effect, pdkb.pddl.formula.Oneof):
act.new_nondet_effect()
for eff in get_arg_list(nondet_eff, pdkb.pddl.formula.And):
condp = PDKB(depth, agents, props)
condn = PDKB(depth, agents, props)
if isinstance(eff, pdkb.pddl.formula.When):
for l in get_arg_list(eff.condition, pdkb.pddl.formula.And):
if isinstance(l, pdkb.pddl.formula.Not):
condn.add_rml(prim2rml(l))
else:
condp.add_rml(prim2rml(l))
lit = prim2rml(eff.result)
if isinstance(eff.result, pdkb.pddl.formula.Not):
act.add_neg_effect(condp, condn, lit)
else:
act.add_pos_effect(condp, condn, lit)
else:
if isinstance(eff, pdkb.pddl.formula.Not):
act.add_neg_effect(condp, condn, prim2rml(eff))
else:
act.add_pos_effect(condp, condn, prim2rml(eff))
return act
def apply_effect(self, state, poseff, negeff):
new_rmls = set([rml for rml in state.rmls])
for condeff in negeff:
if condeff.fires(state) and condeff.eff in new_rmls:
new_rmls.remove(condeff.eff)
for condeff in poseff:
if condeff.fires(state):
new_rmls.add(condeff.eff)
new_state = PDKB(state.depth, state.agents, state.props)
for rml in new_rmls:
new_state.add_rml(rml)
return new_state
def test7():
print "-- START TEST 7 --"
AxiomSystem.SYSTEM = KD
kb = PDKB(1, [1,2,3], map(Literal, ['p', 'q']))
test_remove(kb)
kb = IndexedPDKB(1, [1,2,3], map(Literal, ['p', 'q']))
test_remove(kb)
AxiomSystem.SYSTEM = KT
kb = PDKB(1, [1,2,3], map(Literal, ['p', 'q']))
test_remove_kt(kb)
kb = IndexedPDKB(1, [1,2,3], map(Literal, ['p', 'q']))
test_remove_kt(kb)
print "-- END TEST 7 --\n"
def parse_init(self, prob):
self.init = PDKB(self.domain.depth, self.domain.agents,
self.domain.props)
assume_closed = False
if prob.init_type == 'complete':
assume_closed = True
assert isinstance(prob.init, pdkb.pddl.formula.And)
for prim in prob.init.args:
init_rmls = [prim2rml(prim, False)]
for t in prob.types:
going = True
while going:
new_init_rmls = []
going = False
for old_init_rml in init_rmls:
if "$%s$" % t not in old_init_rml:
new_init_rmls.append(old_init_rml)
else:
going = True
for v in prob.type_to_obj[t]:
# Only do a single split so we can reuse the same variable type
lside = old_init_rml[:old_init_rml.
index("$%s$" % t)]
rside = old_init_rml[old_init_rml.
index("$%s$" % t) +
len("$%s$" % t):]
new_init_rmls.append(lside + v + rside)
init_rmls = new_init_rmls
for rml_line in init_rmls:
self.init.add_rml(parse_rml(rml_line))
# Close the initial state
self.init.logically_close()
if assume_closed:
self.init.close_omniscience()
assert self.init.is_consistent(), "Error: Inconsistent initial state"
def test9():
print("-- START TEST 9 --")
for axiom_system in [KD, KT]:
AxiomSystem.SYSTEM = axiom_system
kb1 = PDKB(3, [1,2,3], list(map(Literal, ['p', 'q', 'r'])))
kb2 = IndexedPDKB(3, [1,2,3], list(map(Literal, ['p', 'q', 'r'])))
test_consistency(kb1, kb2)
print("-- END TEST 9 --\n")
def test10():
print "-- START TEST 10 --"
for axiom_system in [KD, KT]:
AxiomSystem.SYSTEM = axiom_system
kb1 = PDKB(3, [1,2,3,4], map(Literal, ['p', 'q', 'r']))
kb2 = IndexedPDKB(3, [1,2,3,4], map(Literal, ['p', 'q', 'r']))
test_consistency_random_kb(kb1, kb2)
print "-- END TEST 10 --\n"
def preprocess(self):
# Project the initial state
new_init = PDKB(self.init.depth, self.init.agents, self.init.props)
rmls = self.init.rmls
for ag in self.agent_projection:
rmls = project(rmls, ag)
new_init.rmls = rmls
self.init = new_init
# Expand and project the action's effects with derived conditional effects
for act in self.domain.actions:
act.expand()
for ag in self.agent_projection:
act.project_effects(ag)
if self.agent_projection:
# We project the precondition separately since we are in the
# perspective of the final agent
act.project_pre(self.agent_projection[-1])
def test8():
print "-- START TEST 8 --"
for axiom_system in [KD, KT]:
AxiomSystem.SYSTEM = axiom_system
kb = PDKB(1, [1,2], map(Literal, ['p', 'q']))
test_update(kb)
indexed_kb = IndexedPDKB(1, [1,2], map(Literal, ['p', 'q']))
test_update(indexed_kb)
print "-- END TEST 8 --\n"
def test_consistency_random_kb(pdkb, kb):
assert isinstance(pdkb, PDKB)
NUM_RUNS = 10000
fluents = map(Literal, 'pqrst')
agents = list(range(1, 4))
added = []
for i in range(0, NUM_RUNS):
print >> sys.stderr, str(i) + " ",
kb.reset()
pdkb.reset()
rmls = [
random_rml(4, agents, fluents),
random_rml(3, agents, fluents),
random_rml(2, agents, fluents),
]
# Only add the RMLs if they are consistent
check_consistency = PDKB(4, agents, fluents)
check_consistency.update(set(rmls))
if check_consistency.is_consistent():
assert pdkb.is_consistent()
kb_copy = kb.copy()
pdkb_copy = pdkb.copy()
pdkb.update(set(rmls))
kb.update(set(rmls))
rml = compare(pdkb, kb)
if isinstance(rml, RML):
kb_copy.restrict(rml)
pdkb_copy.restrict(rml)
kb.restrict(rml)
pdkb.restrict(rml)
print "before = " + str(kb_copy)
print "before = " + str(pdkb_copy)
print "\t add " + str(rmls)
print "\t after = " + str(kb)
print "\t after = " + str(pdkb)
sys.exit()
def parse_test_pdkb(fname):
lines = read_file(fname)
(depth, num_ag, props) = lines.pop(0).split(' ')
depth = int(depth)
num_ag = int(num_ag)
props = props.split(',')
assert 'B' not in props, "Error: Can't use 'B' as a proposition."
assert num_ag < 10, "Error: Can't use more than 10 agents."
def parse_rml(s):
if '!' == s[0]:
return neg(parse_rml(s[1:]))
elif 'B' == s[0]:
return Belief(int(s[1]), parse_rml(s[2:]))
elif 'P' == s[0]:
return Possible(int(s[1]), parse_rml(s[2:]))
else:
return Literal(s)
rmls = [parse_rml(l.replace(' ', '')) for l in lines[:lines.index('END')]]
desc = "\n".join(lines[lines.index('END') + 1:])
if desc:
print "Running test with the following description:"
print "\n--------\n"
print desc
print "\n-----\n"
kb = PDKB(depth, list(range(1, num_ag + 1)), map(Literal, props))
for rml in rmls:
kb.add_rml(rml)
return rmls
test_kripke(kb, rmls)
def test2():
kb = PDKB(1, [1], map(Literal, ['p', 'q']))
l1 = neg(Literal('p'))
l2 = Belief(1, Literal('p'))
l3 = Belief(1, neg(Literal('q')))
kb.add_rml(l1)
kb.add_rml(l2)
kb.add_rml(l3)
test_kripke(kb, [l1, l2, l3])
def uncertain_changes(condeff, act):
empty = PDKB(act.depth, act.agents, act.props)
condn = PDKB(act.depth, act.agents, act.props)
# Can't have an uncertain firing if there is no condition required
if len(condeff.condp.rmls) == 0:
return []
for rml in condeff.condn.rmls:
condn.add_rml(rml)
for rml in condeff.condp.rmls:
condn.add_rml(neg(rml))
return [(False,
CondEff(empty, condn, neg(condeff.eff), condeff.ma_cond,
('uncertain_firing', 'pos', condeff)))]
def project_pre(self, ag):
assert 0 == len(self.npre), "Cannot project when there is lack-of-belief preconditions"
new_pre = PDKB(self.pre.depth, self.pre.agents, self.pre.props)
for rml in self.pre:
if rml.agent == ag:
if isinstance(rml, Possible):
self.npre.add_rml(neg(rml.rml))
elif isinstance(rml, Belief):
new_pre.add_rml(rml.rml)
else:
assert False, "Trying to project a Literal?"
else:
new_pre.add_rml(rml)
self.pre = new_pre
def test6():
print "-- START TEST 6 --"
for axiom_system in [KD, KT]:
AxiomSystem.SYSTEM = axiom_system
kb1 = PDKB(1, [1,2], map(Literal, ['p', 'q']))
kb2 = PDKB(1, [1,2], map(Literal, ['p', 'q']))
test_expand(kb1, kb2)
# Test that adding an RML already implied does nothing
kb1 = IndexedPDKB(1, [1,2], map(Literal, ['p', 'q']))
kb1.expand(set([Belief(1, Literal('p'))]))
kb2 = kb1.copy()
kb1.expand(set([Possible(1, Literal('p'))]))
assert kb1 == kb2
# Test that adding an RML that implies an existing RML removes that RML
kb1 = IndexedPDKB(1, [1,2], map(Literal, ['p', 'q']))
kb1.expand(set([Possible(1, Literal('p'))]))
old_size = kb1.size()
kb1.expand(set([Belief(1, Literal('p'))]))
assert kb1.size() == old_size, "kb1 = %s, old = %s" % (kb1.size(), old_size)
l1 = Belief(1, Literal('p'))
l2 = Belief(2, Literal('p'))
assert not l1.entails_rml(l2)
for axiom_system in [KD, KT]:
AxiomSystem.SYSTEM = axiom_system
kb1 = IndexedPDKB(1, [1,2], map(Literal, ['p', 'q']))
kb2 = IndexedPDKB(1, [1,2], map(Literal, ['p', 'q']))
test_expand(kb1, kb2)
print "-- END TEST 6 --\n"
class Action(object):
def __init__(self,
name,
depth,
agents,
props,
akprops,
derived_cond,
extra_ancillary=[]):
self.name = name
self.depth = depth
self.agents = agents
self.props = props
self.akprops = akprops
self.derived_cond = derived_cond
self.pre = PDKB(depth, agents, props)
self.npre = PDKB(depth, agents, props)
self.effs = []
# Detect all of the ancillary effects
self.COMPILERS_POS = []
self.COMPILERS_NEG = []
for mod_name in ancillary.compute_modules() + extra_ancillary:
mod = importlib.import_module(mod_name)
self.COMPILERS_POS.extend(mod.COMPILERS_POS)
self.COMPILERS_NEG.extend(mod.COMPILERS_NEG)
def num_effs(self):
count = 0
for eff in self.effs:
count += len(eff[0]) + len(eff[1])
return count
def applicable(self, state, agent=False):
if DEBUG and not (self.pre.rmls <= state.rmls
and 0 == len(self.npre.rmls & state.rmls)):
print("\nDEBUG: Action %s is not applicable" % self.name)
print("Precondition:\n%s" % str(self.pre))
print("State:\n%s\n" % str(state))
return (self.pre.rmls <= state.rmls) and (0 == len(self.npre.rmls
& state.rmls))
def possibly_applicable(self, state):
assert False, "Not Implemented"
def apply(self, state):
return [self.apply_effect(state, eff[0], eff[1]) for eff in self.effs]
def apply_effect(self, state, poseff, negeff):
new_rmls = set([rml for rml in state.rmls])
for condeff in negeff:
if condeff.fires(state) and condeff.eff in new_rmls:
new_rmls.remove(condeff.eff)
for condeff in poseff:
if condeff.fires(state):
new_rmls.add(condeff.eff)
new_state = PDKB(state.depth, state.agents, state.props)
for rml in new_rmls:
new_state.add_rml(rml)
return new_state
def expand(self, relevant_lits=None):
relevant_lits = relevant_lits or set()
for i in range(len(self.effs)):
self.effs[i] = self._expand(self.effs[i][0], self.effs[i][1],
relevant_lits)
def project_effects(self, ag):
for i in range(len(self.effs)):
self.effs[i] = self._project(self.effs[i][0], ag)
def project_pre(self, ag):
assert 0 == len(
self.npre
), "Cannot project when there is lack-of-belief preconditions"
new_pre = PDKB(self.pre.depth, self.pre.agents, self.pre.props)
for rml in self.pre:
if rml.agent == ag:
if isinstance(rml, Possible):
self.npre.add_rml(neg(rml.rml))
elif isinstance(rml, Belief):
new_pre.add_rml(rml.rml)
else:
assert False, "Trying to project a Literal?"
else:
new_pre.add_rml(rml)
self.pre = new_pre
def _expand(self, effp, effn, relevant_lits):
# Because a negated condition can produce a positive (through belief closure)
# and a positive condition can produce a negative (through lack of knowledge),
# we need to keep a mix of both around for the closure.
condleft = [(True, cond) for cond in effp] + [(False, cond)
for cond in effn]
newposconds = set()
newnegconds = set()
while condleft:
(is_pos, condeff) = condleft.pop(0)
if is_pos and (condeff not in newposconds):
if len(relevant_lits) == 0 or condeff.eff in relevant_lits:
newposconds.add(condeff)
for compiler in self.COMPILERS_POS:
condleft.extend(compiler(condeff, self))
elif (not is_pos) and (condeff not in newnegconds):
if len(relevant_lits) == 0 or condeff.eff in relevant_lits:
newnegconds.add(condeff)
for compiler in self.COMPILERS_NEG:
condleft.extend(compiler(condeff, self))
return (list(newposconds), list(newnegconds))
def _project(self, effp, ag):
valid_effs = [x for x in effp if x.uniform(ag, self.akprops)]
projected_effs = [eff.project(ag, self.akprops) for eff in valid_effs]
newposconds = []
newnegconds = []
for (ispos, eff) in projected_effs:
if ispos:
newposconds.append(eff)
else:
newnegconds.append(eff)
return (newposconds, newnegconds)
def new_nondet_effect(self):
self.effs.append((set(), set()))
def add_pos_effect(self, condp, condn, lit, cond_ma_cond=False):
self.effs[-1][0].add(CondEff(condp, condn, lit, cond_ma_cond))
def add_neg_effect(self, condp, condn, lit, cond_ma_cond=False):
self.effs[-1][1].add(CondEff(condp, condn, lit, cond_ma_cond))
def add_pre(self, rml, negate=False):
if negate:
self.npre.add_rml(rml)
else:
self.pre.add_rml(rml)
def pddl(self):
toRet = " (:action %s" % self.name
toRet += "\n :precondition (and %s)" % '\n '.join(
["(%s)" % rml.pddl() for rml in self.pre] +
["(not (%s))" % rml.pddl() for rml in self.npre])
if len(self.effs) > 1:
toRet += "\n\n :effect (oneof %s)" % '\n\n\n '.join(["(and\n%s)" % '\n\n'.join([cond.pddl(' ') for cond in eff[0]] + \
[cond.pddl(' ', True) for cond in eff[1]]) for eff in self.effs])
else:
toRet += "\n :effect (and\n%s)" % '\n\n'.join([cond.pddl(' ') for cond in [i[1] for i in sorted([(e.id(), e) for e in self.effs[0][0]])]] + \
[cond.pddl(' ', True) for cond in [i[1] for i in sorted([(e.id(), e) for e in self.effs[0][1]])]])
toRet += ")"
return toRet
condition, spacing, self.eff.pddl())
else:
return reason + spacing + "(when (and %s)\n%s (%s))" % (
condition, spacing, self.eff.pddl())
if __name__ == '__main__':
a = Action('foo', 2, [1, 2], list(map(Literal, [
'p',
'q',
])), True)
a.add_pre(Belief(1, Literal('p')))
a.add_pre(Belief(2, Literal('p')))
a.new_nondet_effect()
p1 = PDKB(2, [1, 2], list(map(Literal, [
'p',
'q',
])))
p2 = PDKB(2, [1, 2], list(map(Literal, [
'p',
'q',
])))
p3 = PDKB(2, [1, 2], list(map(Literal, [
'p',
'q',
])))
p4 = PDKB(2, [1, 2], list(map(Literal, [
'p',
'q',
])))
pempty = PDKB(2, [1, 2], list(map(Literal, [
'p',
def test1():
print "\n----\n"
l1 = Literal('p')
l2 = Belief(2, Belief(1, l1))
l3 = Belief(2, neg(Belief(1, neg(l1))))
l4 = neg(l3)
l5 = neg(Belief(1, neg(Belief(2, l1))))
l6 = neg(Belief(1, neg(Belief(2, Possible(3, Belief(4, l1))))))
print "KD closure operation:"
print "%s -> %s" % (str(l2), str(map(str, kd_closure(l2))))
print "%s -> %s" % (str(l3), str(map(str, kd_closure(l3))))
print "\n----\n"
kb = PDKB(2, [1,2], map(Literal, ['p', 'q']))
kb.add_rml(l2)
print "Initial KB:"
print kb
print "\nClosing..."
kb.logically_close()
print kb
print "\n----\n"
kb.add_rml(l4)
print "Initial Closed KB:"
kb.logically_close()
print kb
print "\nConsistent: %s" % str(kb.is_consistent())
print "\n----\n"
kb = PDKB(2, [1,2], map(Literal, ['p', 'q']))
kb.add_rml(Belief(1, Literal('p')))
kb.add_rml(Belief(2, Literal('q')))
kb.add_rml(Belief(1, Belief(2, Literal('q'))))
kb.add_rml(neg(Belief(1, Literal('q'))))
print "Initial KB:"
print kb
print "\n...projecting on agent 1\n"
print project(kb.rmls, 1)
print "\n----\n"
def commonly_known_effect(condeff,
agents,
depth,
props,
akprops,
posneg,
schema,
negated=False):
if (schema is False) or (condeff.depth >= depth):
return []
condeffs = []
if schema is True:
schema = [[], []]
if condeff.ma_cond:
schema[0].extend(condeff.ma_cond[0])
schema[1].extend(condeff.ma_cond[1])
for ag in agents:
# We can't remove belief we don't have.
# E.g., (-) p -> B1 q and (-) p -> !B1 q together state that
# when p holds, we're not sure if 1 believes q or not.
# When introspecting for agent 1, it doesn't make sense
# to try and consider (+) B1 p -> !B1 !B1 q as that would
# make (+) B1 p -> B1 q, which when projected would be
# (+) p -> q. Definitely an undesired result.
#if ag == condeff.eff.agent and isinstance(condeff.eff, Not) and negated:
if ag == condeff.eff.agent and negated:
#print "Warning: Ignoring the commonly known extension for the following conditional effect:\n%s" % str(condeff)
continue
condp = PDKB(depth, agents, props)
condn = PDKB(depth, agents, props)
for rml in condeff.condp:
if rml.is_lit() and rml.is_ak(akprops):
condp.add_rml(rml)
else:
condp.add_rml(Belief(ag, rml).merge_modalities())
for rml in condeff.condn:
if rml.is_lit() and rml.is_ak(akprops):
condp.add_rml(neg(rml))
else:
condp.add_rml(neg(Belief(ag, rml)).merge_modalities())
for rmlscheme in schema[0]:
rml = parse_rml(ag.join(rmlscheme.split('?')))
if rml.is_lit() and rml.is_ak(akprops):
condp.add_rml(rml)
else:
condp.add_rml(Belief(ag, rml).merge_modalities())
for rmlscheme in schema[1]:
rml = parse_rml(ag.join(rmlscheme.split('?')))
if rml.is_lit() and rml.is_ak(akprops):
condp.add_rml(rml)
else:
condp.add_rml(neg(Belief(ag, rml)).merge_modalities())
if condeff.eff.is_ak(akprops):
new_eff = condeff.eff
else:
new_eff = Belief(ag, condeff.eff).merge_modalities()
if negated:
new_eff = neg(new_eff)
# Only add the new conditional effect if it is different (this may not
# be the case if there was some introspection removed)
new_cond = CondEff(condp, condn, new_eff, condeff.ma_cond,
('commonly_known', posneg, condeff))
if new_cond != condeff:
condeffs.append((True, new_cond))
return condeffs
