问题
I'm trying to influence the randomness of results for model values generated by Z3. As far as I understand, the options for this are very limited: in case of linear arithmetic, the simplex solver does not allow for random results that still satisfy the given constraints. However, there is an option smt.arith.random_initial_value ("use random initial values in the simplex-based procedure for linear arithmetic (default: false)") which I don't seem to get working:
from z3 import *
set_option('smt.arith.random_initial_value',True)
x = Int('x')
y = Int('y')
s = Solver()
s.add( x+y > 0)
s.check()
s.model()
This seems to always produce [y = 0, x = 1] as a result. Even model completion for variables unused in the given constraints seems to produce deterministic results all the time.
Any ideas or hints about how this option works?
回答1:
Thanks for catching that! There was indeed a bug that caused the random seed not to be passed through to the arithmetic theory. This is now fixed in the unstable branch (fix here).
This example:
(set-option :smt.arith.random_initial_value true)
(declare-const x Int)
(declare-const y Int)
(assert (> (+ x y) 0))
(check-sat-using (using-params qflra :random_seed 1))
(get-model)
(check-sat-using (using-params qflra :random_seed 2))
(get-model)
(check-sat-using (using-params qflra :random_seed 3))
(get-model)
Now produces three different models:
sat
model
(define-fun y () Int
4294966763)
(define-fun x () Int
4294966337)
)
sat
(model
(define-fun y () Int
216)
(define-fun x () Int
4294966341)
)
sat
(model
(define-fun y () Int
196)
(define-fun x () Int
4294966344)
)
It looks like there may be another place where this option isn't passed through correctly (e.g., when using set-logic instead of calling the qflra tactic directly), we're still looking into that.
来源:https://stackoverflow.com/questions/24327987/z3-randomness-of-generated-model-values