Exemple #1
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 def compute_ip_node_values(self, example, test=False):
     '''computes value of input nodes using proof tree'''
     predicate = example.split(" ")[0]
     facts = self.train_facts
     if test:
         facts = self.test_facts
     literal_name = predicate.split("(")[0]
     predicate_time_label = predicate[-2]
     clause_head = ""
     nodes = self.get_nodes()
     for node in nodes:
         rule = node.get_clause()
         rule_body = rule.split(";")
         for item in rule_body:
             item_name = item.split("(")[0]
             item_time_label = item[-2]
             if item_name == literal_name and item_time_label == predicate_time_label:
                 clause_head = item
     sets = self.get_sets_ip_nodes()
     for s in sets:
         clause_body = ""
         for node in s:
             if node.is_input():
                 clause_body += node.get_clause().replace(";", ",") + ","
         clause = clause_head + ":-" + clause_body[:-1]
         if clause_body[:-1] != "true":
             truth = Prover.prove(facts, predicate, clause)
         for node in s:
             if node.is_input():
                 node.set_value(int(truth))
Exemple #2
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 def computeAdviceGradient(example):
     '''computes the advice gradients as nt-nf'''
     nt, nf = 0, 0
     target = Utils.data.target.split('(')[0]
     for clause in Utils.data.adviceClauses:
         if Prover.prove(Utils.data, example, clause):
             if target in Utils.data.adviceClauses[clause]['preferred']:
                 nt += 1
             if target in Utils.data.adviceClauses[clause]['nonPreferred']:
                 nf += 1
     return (nt - nf)
Exemple #3
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 def inferTreeValue(clauses,query,data):
     '''returns probability of query
        given data and clauses learned
     '''
     for clause in clauses: #for every clause in the tree
         clauseCopy = deepcopy(clause)
         clauseValue = float(clauseCopy.split(" ")[1])
         clauseRule = clauseCopy.split(" ")[0].replace(";",",")
         if not clauseRule.split(":-")[1]:
             return clauseValue
         if Prover.prove(data,query,clauseRule): #check if query satisfies clause
             return clauseValue
Exemple #4
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def compute_tree_distance_value(facts, action):
    '''computes shaping reward based on shaping function'''
    f_lines, f_value = [], 0
    with open("tree_distance.txt") as f:
        f_lines = f.read().splitlines()
    for f_line in f_lines:
        potential = float(f_line.split(" ")[0])
        clause = f_line.split(" ")[1].replace(";", ",")
        action_literal = clause.split(":-")[0].split("(")[0]
        if action_literal == action.split("(")[0]:
            if Prover.prove(facts, action, clause):
                f_value = potential
    return f_value
 def getTrueExamples(self,clause,test,data):
     '''returns all examples that satisfy clause
        with conjoined test literal
     '''
     tExamples = [] #intialize list of true examples
     clauseCopy = deepcopy(clause)
     if clauseCopy[-1] == "-": #construct clause for prover
         clauseCopy += test
     elif clauseCopy[-1] == ';':
         clauseCopy = clauseCopy.replace(';',',')+test
     print ("testing clause: ",clauseCopy) # --> to keep track of output, following for loop can be parallelized
     for example in self.examples:
         if Prover.prove(data,example,clauseCopy): #prove if example satisfies clause
             tExamples.append(example)
     return tExamples