def main():
numQueries = 0
queries = []
numTruths = 0
truths = []
with open("./input.txt") as inp:
line = inp.readline()
# First line is always the number of queries
numQueries = int(line)
# n queries
for i in range(numQueries):
line = inp.readline()
queries.append(line.strip())
line = inp.readline()
# This is followed by the number of truths
numTruths = int(line)
for i in range(numTruths):
line = inp.readline()
truths.append(line.strip())
kb = KnowledgeBase(truths)
results = []
for q in queries:
lit = Literal(q, len(truths) + 1)
lit.negate()
result = kb.proveByResolution2([lit], 0)
print("{}: {}".format(q, result))
results.append(str(result).upper())
with open('./output.txt', 'w') as op:
op.write('\n'.join([r for r in results]))
def getProofByResolution(self, l: Literal):
l.negate() # Negate the literal!
inputLiterals = [l]
literalCopy = deepcopy(self.literalMap)
sentenceCopy = deepcopy(self.sentences)
alreadySelected = {}
while True:
# Iterate though all input literals to get the best matching sentence in KB
sentenceCountMap = {}
bestSentence = -1
for inlit in inputLiterals:
key = (inlit.identifier, inlit.litType)
locations = literalCopy.get(key, [])
for loc in locations:
sentence = sentenceCopy[loc]
literals = sentence.literals
for lit in literals:
if (lit.identifier, lit.litType) == key and (
lit.canBeResolvedBy(inlit)
or inlit.canBeResolvedBy(lit)
) and lit.negated != inlit.negated:
# These can be resolved
sentenceCountMap[loc] = sentenceCountMap.get(
loc, 0) + 1
if sentenceCountMap[loc] > sentenceCountMap.get(
bestSentence, -1):
bestSentence = loc
break
# There is no sentence with at least one of the appropriate literals
if bestSentence == -1:
return False
neededSentence = sentenceCopy[bestSentence]
inputLiterals = getResolution(neededSentence, inputLiterals)
if len(inputLiterals) == 0:
self.sentences.append(Sentence(str(l)))
self.literalMap[(l.identifier,
l.litType)] = self.literalMap.get(
(l.identifier, l.litType),
[]) + [len(self.sentences) - 1]
return True
