/
"""Inference in propositional logic"""
from sympy.logic.boolalg import And, Or, Not, Implies, Equivalent, \
conjuncts, to_cnf
from sympy.core.basic import C
from sympy.core.sympify import sympify
def literal_symbol(literal):
"""
The symbol in this literal (without the negation).
Examples:
>>> from sympy import Symbol
>>> from sympy.abc import A
>>> from sympy.logic.inference import literal_symbol
>>> literal_symbol(A)
A
>>> literal_symbol(~A)
A
"""
if literal.func is Not:
return literal.args[0]
else:
return literal
[docs]def satisfiable(expr, algorithm="dpll2"):
"""
Check satisfiability of a propositional sentence.
Returns a model when it succeeds
Examples:
>>> from sympy.abc import A, B
>>> from sympy.logic.inference import satisfiable
>>> satisfiable(A & ~B)
{A: True, B: False}
>>> satisfiable(A & ~A)
False
"""
expr = to_cnf(expr)
if algorithm == "dpll":
from sympy.logic.algorithms.dpll import dpll_satisfiable
return dpll_satisfiable(expr)
elif algorithm == "dpll2":
from sympy.logic.algorithms.dpll2 import dpll_satisfiable
return dpll_satisfiable(expr)
raise NotImplementedError
def pl_true(expr, model={}):
"""
Return True if the propositional logic expression is true in the model,
and False if it is false. If the model does not specify the value for
every proposition, this may return None to indicate 'not obvious';
this may happen even when the expression is tautological.
The model is implemented as a dict containing the pair symbol, boolean value.
Examples
========
>>> from sympy.abc import A, B
>>> from sympy.logic.inference import pl_true
>>> pl_true( A & B, {A: True, B : True})
True
"""
if isinstance(expr, bool):
return expr
expr = sympify(expr)
if expr.is_Symbol:
return model.get(expr)
args = expr.args
func = expr.func
if func is Not:
p = pl_true(args[0], model)
if p is None: return None
else: return not p
elif func is Or:
result = False
for arg in args:
p = pl_true(arg, model)
if p == True: return True
if p == None: result = None
return result
elif func is And:
result = True
for arg in args:
p = pl_true(arg, model)
if p == False: return False
if p == None: result = None
return result
elif func is Implies:
p, q = args
return pl_true(Or(Not(p), q), model)
elif func is Equivalent:
p, q = args
pt = pl_true(p, model)
if pt == None:
return None
qt = pl_true(q, model)
if qt == None:
return None
return pt == qt
else:
raise ValueError("Illegal operator in logic expression" + str(expr))
class KB(object):
"""Base class for all knowledge bases"""
def __init__(self, sentence=None):
self.clauses = []
if sentence:
self.tell(sentence)
def tell(self, sentence):
raise NotImplementedError
def ask(self, query):
raise NotImplementedError
def retract(self, sentence):
raise NotImplementedError
class PropKB(KB):
"""A KB for Propositional Logic. Inefficient, with no indexing."""
def tell(self, sentence):
"""Add the sentence's clauses to the KB
Examples
========
>>> from sympy.logic.inference import PropKB
>>> from sympy.abc import x, y
>>> l = PropKB()
>>> l.clauses
[]
>>> l.tell(x | y)
>>> l.clauses
[Or(x, y)]
>>> l.tell(y)
>>> l.clauses
[Or(x, y), y]
"""
for c in conjuncts(to_cnf(sentence)):
if not c in self.clauses: self.clauses.append(c)
def ask(self, query):
"""Checks if the query is true given the set of clauses.
Examples
========
>>> from sympy.logic.inference import PropKB
>>> from sympy.abc import x, y
>>> l = PropKB()
>>> l.tell(x & ~y)
>>> l.ask(x)
True
>>> l.ask(y)
False
"""
if len(self.clauses) == 0: return False
from sympy.logic.algorithms.dpll import dpll
query_conjuncts = self.clauses[:]
query_conjuncts.extend(conjuncts(to_cnf(query)))
s = set()
for q in query_conjuncts:
s = s.union(q.atoms(C.Symbol))
return bool(dpll(query_conjuncts, list(s), {}))
def retract(self, sentence):
"""Remove the sentence's clauses from the KB
Examples
========
>>> from sympy.logic.inference import PropKB
>>> from sympy.abc import x, y
>>> l = PropKB()
>>> l.clauses
[]
>>> l.tell(x | y)
>>> l.clauses
[Or(x, y)]
>>> l.retract(x | y)
>>> l.clauses
[]
"""
for c in conjuncts(to_cnf(sentence)):
if c in self.clauses:
self.clauses.remove(c)