def add_rules(model):
model.add_rule(Rule("10: Block(P1, A) & Block(P2, A) & Similar(P1, P2) & P1 != P2 -> Friends(P1, P2) ^2"))
model.add_rule(Rule("10: Block(P1, A) & Block(P2, A) & Block(P3, A) & Friends(P1, P2) & Friends(P2, P3) & P1 != P2 & P2 != P3 & P1 != P3 -> Friends(P1, P3) ^2"))
model.add_rule(Rule("10: Block(P1, A) & Block(P2, A) & Friends(P1, P2) & P1 != P2 -> Friends(P2, P1) ^2"))
# Negative prior.
model.add_rule(Rule("1: !Friends(P1, P2) ^2"))
def similarity(model, combination=False, squared=True):
if not combination:
model.add_rule(
Rule("1.0: Knows(A, B) & Prior('0') -> Trusts(A, B)",
squared=squared))
model.add_rule(
Rule("1.0: Knows(A, B) & Trusts(A, B) -> Prior('0')",
squared=squared))
model.add_rule(
Rule("1.0: Knows(A, B) & SameTastes(A, B) & (A != B) -> Trusts(A, B)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & !SameTastes(A, B) & (A != B) -> !Trusts(A, B)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(A, C) & Trusts(A, B) & SameTastes(B, C) & (A != B) & (B != C) & (A != C) -> Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(A, C) & !Trusts(A, B) & SameTastes(B, C) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, C) & Knows(B, C) & Trusts(A, C) & SameTastes(A, B) & (A != B) & (B != C) & (A != C) -> Trusts(B, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, C) & Knows(B, C) & !Trusts(A, C) & SameTastes(A, B) & (A != B) & (B != C) & (A != C) -> !Trusts(B, C)",
squared=squared))
def personality_rules(model, combination=False, squared=True):
model.add_rule(
Rule("1.0: Knows(A, B) & Trusts(A, B) -> TrustWorthy(B)",
squared=squared))
model.add_rule(
Rule("1.0: Knows(A, B) & Trusts(A, B) -> Trusting(A)",
squared=squared))
model.add_rule(
Rule("1.0: Knows(A, B) & !Trusts(A, B) -> !TrustWorthy(B)",
squared=squared))
model.add_rule(
Rule("1.0: Knows(A, B) & !Trusts(A, B) -> !Trusting(A)",
squared=squared))
model.add_rule(
Rule("1.0: Knows(A, B) & Trusting(A) & TrustWorthy(B) -> Trusts(A, B)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & !Trusting(A) & !TrustWorthy(B) -> !Trusts(A, B)",
squared=squared))
if not combination:
model.add_rule(
Rule("1.0: Knows(A, B) & Prior('0') -> Trusts(A, B)",
squared=squared))
model.add_rule(
Rule("1.0: Knows(A, B) & Trusts(A, B) -> Prior('0')",
squared=squared))
def _add_rules(self, model, relations):
"""
Add rules connecting entities together.
"""
model.add_rule(Rule('1.0: ~spam_msg(M) ^2'))
model.add_rule(Rule('1.0: prior_msg(M) -> spam_msg(M) ^2'))
for relation in relations:
var = relation[0].upper()
r1 = '1.0: has_{}(M, {}) & spam_{}({}) -> spam_msg(M) ^2'
r2 = '1.0: has_{}(M, {}) & spam_msg(M) -> spam_{}({}) ^2'
model.add_rule(Rule('1.0: ~spam_{}({}) ^2'.format(relation, var)))
model.add_rule(Rule(r1.format(relation, var, relation, var)))
model.add_rule(Rule(r2.format(relation, var, relation, var)))
def add_rules(model):
# Neighborhood rules.
model.add_rule(
Rule("1.0: HasCat(A, C) & Link(A, B) & (A != B) >> HasCat(B, C) ^2"))
model.add_rule(
Rule("1.0: HasCat(A, C) & Link(B, A) & (A != B) >> HasCat(B, C) ^2"))
# Per category rules
for i in range(NUM_CATEGORIES):
# Categories are 1-indexed.
rule_string = "HasCat(A, '%d') & Link(A, B) >> HasCat(B, '%d')" % (
i + 1, i + 1)
model.add_rule(Rule(rule_string, weight=1.0, squared=True))
# Ensure that HasCat sums to 1
model.add_rule(Rule("HasCat(A, +C) = 1 ."))
# Prior
model.add_rule(Rule("0.001: !HasCat(A, N) ^2"))
def add_rules(model):
model.add_rule(Rule("0.50: Bias(A, P) >> Votes(A, P) ^2"))
model.add_rule(
Rule("0.30: Votes(A, P) & KnowsWell(B, A) >> Votes(B, P) ^2"))
model.add_rule(Rule("0.10: Votes(A, P) & Knows(B, A) >> Votes(B, P) ^2"))
model.add_rule(Rule("0.05: Votes(A, P) & Boss(B, A) >> Votes(B, P) ^2"))
model.add_rule(Rule("0.10: Votes(A, P) & Mentor(B, A) >> Votes(B, P) ^2"))
model.add_rule(
Rule("0.70: Votes(A, P) & OlderRelative(B, A) >> Votes(B, P) ^2"))
model.add_rule(Rule("0.80: Votes(A, P) & Idol(B, A) >> Votes(B, P) ^2"))
# Negative prior
model.add_rule(Rule("0.01: !Votes(A, P) ^2"))
# Partial functional on votes.
model.add_rule(Rule("Votes(A, +B) <= 1 ."))
def add_rules(model):
# Look for text similarity.
model.add_rule(
Rule(
"40.0: AuthorName(A1, N1) & AuthorName(A2, N2) & SimName(N1, N2) & (A1 != A2) -> SameAuthor(A1, A2) ^2"
))
model.add_rule(
Rule(
"40.0: PaperTitle(P1, T1) & PaperTitle(P2, T2) & SimTitle(T1, T2) & (P1 != P2) -> SamePaper(P1, P2) ^2"
))
# Pure transitivity
model.add_rule(
Rule("""
20.0: AuthorBlock(A1, B) & AuthorBlock(A2, B) & AuthorBlock(A3, B)
& SameAuthor(A1, A2) & SameAuthor(A2, A3)
& (A1 != A3) & (A1 != A2) & (A2 != A3)
-> SameAuthor(A1, A3) ^2
"""))
# Coauthor rectangle closure.
model.add_rule(
Rule("""
20.0: AuthorBlock(A1, B1) & AuthorBlock(A2, B1) & AuthorBlock(CA1, B2) & AuthorBlock(CA2, B2) &
& AuthorOf(A1, P1) & AuthorOf(A2, P2)
& AuthorOf(CA1, P1) & AuthorOf(CA2, P2) & SameAuthor(CA1, CA2)
& (A1 != CA1) & (A2 != CA2) & (P1 != P2)
-> SameAuthor(A1, A2) ^2
"""))
# Paper rectangle closure.
model.add_rule(
Rule("""
10.0: AuthorBlock(A1, B1) & AuthorBlock(A2, B1)
& AuthorOf(A1, P1) & AuthorOf(A2, P2)
& SamePaper(P1, P2)
-> SameAuthor(A1, A2) ^2
"""))
# Self-refernece.
model.add_rule(Rule("SameAuthor(A, A) = 1.0 ."))
model.add_rule(Rule("SamePaper(P, P) = 1.0 ."))
# Negative priors.
model.add_rule(Rule("1.0: !SameAuthor(A1, A2) ^2"))
model.add_rule(Rule("1.0: !SamePaper(A1, A2) ^2"))
def add_rules (model):
model.add_rule(Rule("20: Lived(P1, L) & Lived(P2, L) & (P1 != P2) -> Knows(P1, P2) ^2"))
model.add_rule(Rule("5: Lived(P1, L1) & Lived(P2, L2) & (P1 != P2) & (L1 != L2) -> !Knows(P1, P2) ^2"))
model.add_rule(Rule("10: Likes(P1, L) & Likes(P2, L) & (P1 != P2) -> Knows(P1, P2) ^2"))
model.add_rule(Rule("5: Knows(P1, P2) & Knows(P2, P3) & (P1 != P3) -> Knows(P1, P3) ^2"))
model.add_rule(Rule("Knows(P1, P2) = Knows(P2, P1) ."))
model.add_rule(Rule("5: !Knows(P1, P2) ^2"))
def add_rules(model):
model.add_rule(Rule('20: Lived(P1, L) & Lived(P2, L) & (P1 != P2) -> Knows(P1, P2) ^2'))
model.add_rule(Rule('5: Lived(P1, L1) & Lived(P2, L2) & (P1 != P2) & (L1 != L2) -> !Knows(P1, P2) ^2'))
model.add_rule(Rule('10: Likes(P1, L) & Likes(P2, L) & (P1 != P2) -> Knows(P1, P2) ^2'))
model.add_rule(Rule('5: Knows(P1, P2) & Knows(P2, P3) & (P1 != P3) -> Knows(P1, P3) ^2'))
model.add_rule(Rule('Knows(P1, P2) = Knows(P2, P1) .'))
model.add_rule(Rule('5: !Knows(P1, P2) ^2'))
def test_load_from_file(self):
path = os.path.join(PSLTest.SIMPLE_ACQUAINTANCES_PSL_DIR, 'simple-acquaintances.psl')
rules = Rule.load_from_file(path)
expected = [
'20.00: Lived(P1, L) & Lived(P2, L) & (P1 != P2) -> Knows(P1, P2) ^2',
'5.00: Lived(P1, L1) & Lived(P2, L2) & (P1 != P2) & (L1 != L2) -> !Knows(P1, P2) ^2',
'10.00: Likes(P1, L) & Likes(P2, L) & (P1 != P2) -> Knows(P1, P2) ^2',
'5.00: Knows(P1, P2) & Knows(P2, P3) & (P1 != P3) -> Knows(P1, P3) ^2',
'Knows(P1, P2) = Knows(P2, P1) .',
'5.00: !Knows(P1, P2) ^2',
]
self.assertEquals(len(rules), len(expected))
for i in range(len(rules)):
self.assertEquals(rules[i].to_string(2), expected[i])
def run():
model = Model(MODEL_NAME)
# Add Predicates
knows_predicate = Predicate('Knows', closed=False, size=2)
model.add_predicate(knows_predicate)
likes_predicate = Predicate('Likes', closed=True, size=2)
model.add_predicate(likes_predicate)
lived_predicate = Predicate('Lived', closed=True, size=2)
model.add_predicate(lived_predicate)
# Add Data
path = os.path.join(DATA_DIR, 'knows_obs.txt')
knows_predicate.add_data_file(Partition.OBSERVATIONS, path)
path = os.path.join(DATA_DIR, 'lived_obs.txt')
lived_predicate.add_data_file(Partition.OBSERVATIONS, path)
path = os.path.join(DATA_DIR, 'likes_obs.txt')
likes_predicate.add_data_file(Partition.OBSERVATIONS, path)
path = os.path.join(DATA_DIR, 'knows_targets.txt')
knows_predicate.add_data_file(Partition.TARGETS, path)
path = os.path.join(DATA_DIR, 'knows_truth.txt')
knows_predicate.add_data_file(Partition.TRUTH, path)
# Add Rules
model.add_rule(
Rule('20: Lived(P1, L) & Lived(P2, L) & (P1 != P2) -> Knows(P1, P2) ^2'
))
model.add_rule(
Rule(
'5: Lived(P1, L1) & Lived(P2, L2) & (P1 != P2) & (L1 != L2) -> !Knows(P1, P2) ^2'
))
model.add_rule(
Rule('10: Likes(P1, L) & Likes(P2, L) & (P1 != P2) -> Knows(P1, P2) ^2'
))
model.add_rule(
Rule(
'5: Knows(P1, P2) & Knows(P2, P3) & (P1 != P3) -> Knows(P1, P3) ^2'
))
model.add_rule(Rule('Knows(P1, P2) = Knows(P2, P1) .'))
model.add_rule(Rule('5: !Knows(P1, P2) ^2'))
# Run Inference
results = model.infer(psl_config=ADDITIONAL_PSL_OPTIONS)
return results
def balance5rules(model, recip=False, squared=True):
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(B, C) & Knows(A, C) & Trusts(A, B) & Trusts(B, C) & (A != B) & (B != C) & (A != C) -> Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(B, C) & Knows(A, C) & Trusts(A, B) & !Trusts(B, C) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(B, C) & Knows(A, C) & !Trusts(A, B) & !Trusts(B, C) & (A != B) & (B != C) & (A != C) -> Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(C, B) & Knows(A, C) & Trusts(A, B) & Trusts(C, B) & (A != B) & (B != C) & (A != C) -> Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(B, A) & Knows(B, C) & Knows(A, C) & Trusts(B, A) & Trusts(B, C) & (A != B) & (B != C) & (A != C) -> Trusts(A, C)",
squared=squared))
# two-sided prior
model.add_rule(
Rule("1.0: Knows(A, B) & Prior('0') -> Trusts(A, B)", squared=squared))
model.add_rule(
Rule("1.0: Knows(A, B) & Trusts(A, B) -> Prior('0')", squared=squared))
if recip:
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(B, A) & Trusts(A, B) -> Trusts(B, A)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(B, A) & !Trusts(A, B) -> !Trusts(B, A)",
squared=squared))
def test_set_weight(self):
rule = Rule('1.0: Nice(A) & Nice(B) & (A != B) -> Friends(A, B) ^2')
self.assertEquals(rule.weight(), 1.0)
rule.set_weight(5.0)
self.assertEquals(rule.weight(), 5.0)
rule.set_weight(0.0)
self.assertEquals(rule.weight(), 0.0)
try:
rule.set_weight(-1.0)
self.fail('No exception when setting negative weight.')
except RuleError as ex:
# Expected
pass
rule = Rule('Nice(A) & Nice(B) & (A != B) -> Friends(A, B) .')
try:
rule.set_weight(1.0)
self.fail('No exception when setting weight of an unweighted rule.')
except RuleError as ex:
# Expected
pass
def status_rules(model, inv=False, squared=True):
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(B, C) & Knows(A, C) & Trusts(A, B) & Trusts(B, C) & (A != B) & (B != C) & (A != C) -> Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(B, C) & Knows(A, C) & !Trusts(A, B) & !Trusts(B, C) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(C, B) & Knows(A, C) & Trusts(A, B) & !Trusts(C, B) & (A != B) & (B != C) & (A != C) -> Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(C, B) & Knows(A, C) & !Trusts(A, B) & Trusts(C, B) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(B, A) & Knows(B, C) & Knows(A, C) & Trusts(B, A) & !Trusts(B, C) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(B, A) & Knows(B, C) & Knows(A, C) & !Trusts(B, A) & Trusts(B, C) & (A != B) & (B != C) & (A != C) -> Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(B, A) & Knows(C, B) & Knows(A, C) & Trusts(B, A) & Trusts(C, B) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(B, A) & Knows(C, B) & Knows(A, C) & !Trusts(B, A) & !Trusts(C, B) & (A != B) & (B != C) & (A != C) -> Trusts(A, C)",
squared=squared))
model.add_rule(
Rule("1.0: Knows(A, B) & Prior('0') -> Trusts(A, B)", squared=squared))
model.add_rule(
Rule("1.0: Knows(A, B) & Trusts(A, B) -> Prior('0')", squared=squared))
if inv:
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(B, A) & Trusts(A, B) -> !Trusts(B, A)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(B, A) & !Trusts(A, B) -> Trusts(B, A)",
squared=squared))
def cyclic_bal_rules(model, unbalanced=False, squared=True):
model.add_rule(
Rule("1.0: Knows(A, B) & Prior('0') -> Trusts(A, B)", squared=squared))
model.add_rule(
Rule("1.0: Knows(A, B) & Trusts(A, B) -> Prior('0')", squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(B, C) & Knows(C, A) & Trusts(A, B) & Trusts(B, C) & (A != B) & (B != C) & (A != C) -> Trusts(C, A)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(B, C) & Knows(C, A) & !Trusts(A, B) & !Trusts(B, C) & (A != B) & (B != C) & (A != C) -> Trusts(C, A)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(A, C) & Knows(C, B) & Trusts(A,B) & Trusts(A,C) & (A != B) & (B != C) & (A != C) -> Trusts(C,B)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(A, C) & Knows(C, B) & Trusts(A,B) & !Trusts(A,C) & (A != B) & (B != C) & (A != C) -> !Trusts(C,B)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(A, C) & Knows(C, B) & !Trusts(A,B) & Trusts(A,C) & (A != B) & (B != C) & (A != C) -> !Trusts(C,B)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & knows(A, C) & knows(C, B) & !Trusts(A,B) & !Trusts(A,C) & (A != B) & (B != C) & (A != C) -> Trusts(C,B)",
squared=squared))
if unbalanced:
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(B, C) & Knows(C, A) & Trusts(A, B) & !Trusts(B, C) & (A != B) & (B != C) & (A != C) -> Trusts(C, A)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(B, C) & Knows(C, A) & Trusts(A, B) & Trusts(B, C) & (A != B) & (B != C) & (A != C) -> !Trusts(C, A)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(A, C) & Knows(C, B) & Trusts(A,B) & Trusts(A,C) & (A != B) & (B != C) & (A != C) -> !Trusts(C,B)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(A, C) & Knows(C, B) & Trusts(A,B) & !Trusts(A,C) & (A != B) & (B != C) & (A != C) -> Trusts(C,B)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(A, C) & Knows(C, B) & !Trusts(A,B) & Trusts(A,C) & (A != B) & (B != C) & (A != C) -> Trusts(C,B)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & knows(A, C) & knows(C, B) & !Trusts(A,B) & !Trusts(A,C) & (A != B) & (B != C) & (A != C) -> !Trusts(C,B)",
squared=squared))
def test_set_squared(self):
rule = Rule('1.0: Nice(A) & Nice(B) & (A != B) -> Friends(A, B) ^2')
self.assertEquals(rule.squared(), True)
rule.set_squared(False)
self.assertEquals(rule.squared(), False)
rule.set_squared(True)
self.assertEquals(rule.squared(), True)
rule = Rule('Nice(A) & Nice(B) & (A != B) -> Friends(A, B) .')
try:
rule.set_squared(True)
self.fail('No exception when squared an unweighted rule.')
except RuleError as ex:
# Expected
pass
def test_init_args(self):
failing_configs = [
({
'rule_string': 'Nice(A) & Nice(B) & (A != B) -> Friends(A, B) .',
'weighted': True
}, 'Unweighted mismatch.'),
({
'rule_string': '1.0: Nice(A) & Nice(B) & (A != B) -> Friends(A, B)',
'weighted': False,
}, 'Weighted mismatch.'),
({
'rule_string': '1.0: Nice(A) & Nice(B) & (A != B) -> Friends(A, B) .',
}, 'Both weighted and unweighted.'),
({
'rule_string': 'Nice(A) & Nice(B) & (A != B) -> Friends(A, B) ^2 .',
}, 'Squared unweighted.'),
({
'rule_string': 'Nice(A) & Nice(B) & (A != B) -> Friends(A, B) . ^2',
}, 'Unweighted squared.'),
({
'rule_string': '1.0: Nice(A) & Nice(B) & (A != B) -> Friends(A, B) . ^2',
}, 'Weight unweighted squared.'),
({
'rule_string': 'Nice(A) & Nice(B) & (A != B) -> Friends(A, B)',
}, 'Missing weight 1.'),
({
'rule_string': 'Nice(A) & Nice(B) & (A != B) -> Friends(A, B)',
'weighted': True,
}, 'Missing weight 2.'),
({
'rule_string': '1.0: Nice(A) & Nice(B) & (A != B) -> Friends(A, B)',
'weight': 0.0,
}, 'Weight mismatch.'),
({
'rule_string': '-1.0: Nice(A) & Nice(B) & (A != B) -> Friends(A, B)',
}, 'Negative weight (string).'),
({
'rule_string': 'Nice(A) & Nice(B) & (A != B) -> Friends(A, B)',
'weight': -1.0,
}, 'Negative weight (arg).'),
({
'rule_string': '1.0: Nice(A) & Nice(B) & (A != B) -> Friends(A, B) ^2',
'squared': False,
}, 'Squred mismatch 1.'),
({
'rule_string': '1.0: Nice(A) & Nice(B) & (A != B) -> Friends(A, B) ^1',
'squared': True,
}, 'Squred mismatch 2.'),
({
'rule_string': 'Nice(A) & Nice(B) & (A != B) -> Friends(A, B)',
'weighted': False,
'squared': True,
}, 'Squred mismatch 2.'),
]
for (args, reason) in failing_configs:
try:
rule = Rule(**args)
self.fail('Failed to raise exception on: ' + reason)
except RuleError as ex:
# Expected
pass
def add_rules(model):
# FFpp
model.add_rule(Rule("1.0: Knows(A, B) & Knows(B, C) & Knows(A, C) & Trusts(A, B) & Trusts(B, C) & (A != B) & (B != C) & (A != C) -> Trusts(A, C) ^2"))
# FFpm
model.add_rule(Rule("1.0: Knows(A, B) & Knows(B, C) & Knows(A, C) & Trusts(A, B) & !Trusts(B, C) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C) ^2"))
# FFmp
model.add_rule(Rule("1.0: Knows(A, B) & Knows(B, C) & Knows(A, C) & !Trusts(A, B) & Trusts(B, C) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C) ^2"))
# FFmm
model.add_rule(Rule("1.0: Knows(A, B) & Knows(B, C) & Knows(A, C) & !Trusts(A, B) & !Trusts(B, C) & (A != B) & (B != C) & (A != C) -> Trusts(A, C) ^2"))
# FBpp
model.add_rule(Rule("1.0: Knows(A, B) & Knows(C, B) & Knows(A, C) & Trusts(A, B) & Trusts(C, B) & (A != B) & (B != C) & (A != C) -> Trusts(A, C) ^2"))
# FBpm
model.add_rule(Rule("1.0: Knows(A, B) & Knows(C, B) & Knows(A, C) & Trusts(A, B) & !Trusts(C, B) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C) ^2"))
# FBmp
model.add_rule(Rule("1.0: Knows(A, B) & Knows(C, B) & Knows(A, C) & !Trusts(A, B) & Trusts(C, B) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C) ^2"))
# FBmm
model.add_rule(Rule("1.0: Knows(A, B) & Knows(C, B) & Knows(A, C) & !Trusts(A, B) & !Trusts(C, B) & (A != B) & (B != C) & (A != C) -> Trusts(A, C) ^2"))
# BFpp
model.add_rule(Rule("1.0: Knows(B, A) & Knows(B, C) & Knows(A, C) & Trusts(B, A) & Trusts(B, C) & (A != B) & (B != C) & (A != C) -> Trusts(A, C) ^2"))
# BFpm
model.add_rule(Rule("1.0: Knows(B, A) & Knows(B, C) & Knows(A, C) & Trusts(B, A) & !Trusts(B, C) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C) ^2"))
# BFmp
model.add_rule(Rule("1.0: Knows(B, A) & Knows(B, C) & Knows(A, C) & !Trusts(B, A) & Trusts(B, C) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C) ^2"))
# BFmm
model.add_rule(Rule("1.0: Knows(B, A) & Knows(B, C) & Knows(A, C) & !Trusts(B, A) & !Trusts(B, C) & (A != B) & (B != C) & (A != C) -> Trusts(A, C) ^2"))
# BBpp
model.add_rule(Rule("1.0: Knows(B, A) & Knows(C, B) & Knows(A, C) & Trusts(B, A) & Trusts(C, B) & (A != B) & (B != C) & (A != C) -> Trusts(A, C) ^2"))
# BBpm
model.add_rule(Rule("1.0: Knows(B, A) & Knows(C, B) & Knows(A, C) & Trusts(B, A) & !Trusts(C, B) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C) ^2"))
# BBmp
model.add_rule(Rule("1.0: Knows(B, A) & Knows(C, B) & Knows(A, C) & !Trusts(B, A) & Trusts(C, B) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C) ^2"))
# BBmm
model.add_rule(Rule("1.0: Knows(B, A) & Knows(C, B) & Knows(A, C) & !Trusts(B, A) & !Trusts(C, B) & (A != B) & (B != C) & (A != C) -> Trusts(A, C) ^2"))
model.add_rule(Rule("1.0: Knows(A, B) & Knows(B, A) & Trusts(A, B) -> Trusts(B, A) ^2"))
model.add_rule(Rule("1.0: Knows(A, B) & Knows(B, A) & !Trusts(A, B) -> !Trusts(B, A) ^2"))
# two-sided prior
model.add_rule(Rule("1.0: Knows(A, B) & Prior('0') -> Trusts(A, B) ^2"))
model.add_rule(Rule("1.0: Knows(A, B) & Trusts(A, B) -> Prior('0') ^2"))
def read_rules_from_file(predicate_path):
for line in predicate_path.open("r").readlines():
yield Rule(line)
def balanceExtended(model, squared=True):
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(B, C) & Knows(A, C) & !Trusts(A, B) & Trusts(B, C) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(C, B) & Knows(A, C) & Trusts(A, B) & !Trusts(C, B) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(C, B) & Knows(A, C) & !Trusts(A, B) & Trusts(C, B) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(A, B) & Knows(C, B) & Knows(A, C) & !Trusts(A, B) & !Trusts(C, B) & (A != B) & (B != C) & (A != C) -> Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(B, A) & Knows(B, C) & Knows(A, C) & Trusts(B, A) & !Trusts(B, C) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(B, A) & Knows(B, C) & Knows(A, C) & !Trusts(B, A) & Trusts(B, C) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(B, A) & Knows(B, C) & Knows(A, C) & !Trusts(B, A) & !Trusts(B, C) & (A != B) & (B != C) & (A != C) -> Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(B, A) & Knows(C, B) & Knows(A, C) & Trusts(B, A) & Trusts(C, B) & (A != B) & (B != C) & (A != C) -> Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(B, A) & Knows(C, B) & Knows(A, C) & Trusts(B, A) & !Trusts(C, B) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(B, A) & Knows(C, B) & Knows(A, C) & !Trusts(B, A) & Trusts(C, B) & (A != B) & (B != C) & (A != C) -> !Trusts(A, C)",
squared=squared))
model.add_rule(
Rule(
"1.0: Knows(B, A) & Knows(C, B) & Knows(A, C) & !Trusts(B, A) & !Trusts(C, B) & (A != B) & (B != C) & (A != C) -> Trusts(A, C)",
squared=squared))
def add_rules(model):
model.add_rule(Rule("025: VALCAT(B, C) & SAMEENTITY(A, B) & CAT(A, C) -> CAT(B, C) ^2"))
model.add_rule(Rule("025: VALREL(B, Z, R) & SAMEENTITY(A, B) & REL(A, Z, R) -> REL(B, Z, R) ^2"))
model.add_rule(Rule("025: VALREL(Z, B, R) & SAMEENTITY(A, B) & REL(Z, A, R) -> REL(Z, B, R) ^2"))
model.add_rule(Rule("100: VALCAT(A, D) & SUB(C, D) & CAT(A, C) -> CAT(A, D) ^2"))
model.add_rule(Rule("100: VALREL(A, B, S) & RSUB(R, S) & REL(A, B, R) -> REL(A, B, S) ^2"))
model.add_rule(Rule("100: VALCAT(A, D) & MUT(C, D) & CAT(A, C) -> !CAT(A, D) ^2"))
model.add_rule(Rule("100: VALREL(A, B, S) & RMUT(R, S) & REL(A, B, R) -> !REL(A, B, S) ^2"))
model.add_rule(Rule("100: VALREL(B, A, S) & INV(R, S) & REL(A, B, R) -> REL(B, A, S) ^2"))
model.add_rule(Rule("100: VALCAT(A, C) & DOMAIN(R, C) & REL(A, B, R) -> CAT(A, C) ^2"))
model.add_rule(Rule("100: VALCAT(B, C) & RANGE2(R, C) & REL(A, B, R) -> CAT(B, C) ^2"))
model.add_rule(Rule("001: VALCAT(A, C) & CANDCAT_GENERAL(A, C) -> CAT(A, C) ^2"))
model.add_rule(Rule("001: VALREL(A, B, R) & CANDREL_GENERAL(A, B, R) -> REL(A, B, R) ^2"))
model.add_rule(Rule("001: VALCAT(A, C) & CANDCAT_CBL(A, C) -> CAT(A, C) ^2"))
model.add_rule(Rule("001: VALREL(A, B, R) & CANDREL_CBL(A, B, R) -> REL(A, B, R) ^2"))
model.add_rule(Rule("001: VALCAT(A, C) & CANDCAT_CMC(A, C) -> CAT(A, C) ^2"))
model.add_rule(Rule("001: VALCAT(A, C) & CANDCAT_CPL(A, C) -> CAT(A, C) ^2"))
model.add_rule(Rule("001: VALREL(A, B, R) & CANDREL_CPL(A, B, R) -> REL(A, B, R) ^2"))
model.add_rule(Rule("001: VALCAT(A, C) & CANDCAT_MORPH(A, C) -> CAT(A, C) ^2"))
model.add_rule(Rule("001: VALCAT(A, C) & CANDCAT_SEAL(A, C) -> CAT(A, C) ^2"))
model.add_rule(Rule("001: VALREL(A, B, R) & CANDREL_SEAL(A, B, R) -> REL(A, B, R) ^2"))
model.add_rule(Rule("001: VALCAT(A, C) & PROMCAT_GENERAL(A, C) -> CAT(A, C) ^2"))
model.add_rule(Rule("001: VALREL(A, B, R) & PROMREL_GENERAL(A, B, R) -> REL(A, B, R) ^2"))
# Priors
model.add_rule(Rule("002: VALCAT(A, C) -> !CAT(A, C) ^2"))
model.add_rule(Rule("002: VALREL(A, B, R) -> !REL(A, B, R) ^2"))
model.add_rule(Rule("001: VALCAT(A, C) -> CAT(A, C) ^2"))
model.add_rule(Rule("001: VALREL(A, B, R) -> REL(A, B, R) ^2"))
def add_rules(model):
# Priors from local classifiers
model.add_rule(
Rule("50: Has(U, S) & Predicts(S, U, A, L) -> Is(U, A, L) ^2"))
model.add_rule(
Rule("50: Has(U, S) & ~Predicts(S, U, A, L) -> ~Is(U, A, L) ^2"))
# Collective Rules for relational signals
model.add_rule(
Rule("100: Joins(U, G) & Joins(V, G) & Is(V, A, L) -> Is(U, A, L) ^2"))
model.add_rule(
Rule("100: Joins(U, G) & Joins(V, G) & ~Is(V, A, L) -> ~Is(U, A, L) ^2"
))
model.add_rule(
Rule("10: Likes(U, T) & Likes(V, T) & Is(V, A, L) -> Is(U, A, L) ^2"))
model.add_rule(
Rule(
"10: Likes(U, T) & Likes(V, T) & ~Is(V, A, L) -> ~Is(U, A, L) ^2"))
model.add_rule(Rule("1: Friend(U, V) & Is(V, A, L)-> Is(U, A, L) ^2"))
model.add_rule(Rule("1: Friend(U, V) & ~Is(V, A, L)-> ~Is(U, A, L) ^2"))
model.add_rule(Rule("1: Friend(V, U) & Is(V, A, L)-> Is(U, A, L) ^2"))
model.add_rule(Rule("1: Friend(V, U) & ~Is(V, A, L)-> ~Is(U, A, L) ^2"))
# Ensure that user has one attribute
model.add_rule(Rule("1: Is(U, A, +L) = 1"))
