鲁滨逊归结原理python代码实现

鲁滨逊归结原理是一种用于判断逻辑命题公式可满足性的方法。下面是一个简单的Python代码实现鲁滨逊归结原理的示例：

# 定义一个函数，用于判断两个子句是否可以进行归结
def can_resolve(clause1, clause2):
    for literal in clause1:
        if literal == 'not':
            neg_literal = literal[2:]
        else:
            neg_literal = 'not' + literal
        if neg_literal in clause2:
            return True
    return False

# 定义一个函数，用于进行归结操作
def resolve(clause1, clause2):
    new_clause = []
    for literal in clause1:
        if literal == 'not':
            neg_literal = literal[2:]
        else:
            neg_literal = 'not' + literal
        if neg_literal not in clause2:
            new_clause.append(literal)
    for literal in clause2:
        if literal == 'not':
            neg_literal = literal[2:]
        else:
            neg_literal = 'not' + literal
        if neg_literal not in clause1:
            new_clause.append(literal)
    return new_clause

# 定义一个函数，用于判断逻辑命题公式是否可满足
def is_satisfiable(clauses):
    while True:
        new_clauses = []
        n = len(clauses)
        for i in range(n):
            for j in range(i+1, n):
                if can_resolve(clauses[i], clauses[j]):
                    resolvent = resolve(clauses[i], clauses[j])
                    if len(resolvent) == 0:
                        return True
                    if resolvent not in new_clauses:
                        new_clauses.append(resolvent)
        if len(new_clauses) == 0:
            return False
        clauses += new_clauses

# 测试代码
clauses = [['not', 'P', 'Q'], ['P'], ['Q']]
print(is_satisfiable(clauses))

上述代码实现了鲁滨逊归结原理的基本逻辑，通过判断两个子句是否可以进行归结，并进行归结操作，最终判断逻辑命题公式是否可满足。在测试代码中，我们定义了一个包含三个子句的逻辑命题公式，通过调用`is_satisfiable`函数来判断其可满足性。