How to encode the optimal vertex cover problem below in Z3/Java?
In particular, how to express the minimize condition?
I could not find a similar example in the Z3/Java examples.
(declare-fun vertex_a () Bool)
(declare-fun vertex_b () Bool)
(declare-fun vertex_c () Bool)
(declare-fun vertex_d () Bool)
(declare-fun vertex_e () Bool)
(declare-fun edge_a_c () Bool)
(declare-fun edge_a_b () Bool)
(declare-fun edge_a_e () Bool)
(declare-fun edge_b_c () Bool)
(declare-fun edge_b_d () Bool)
(declare-fun edge_b_e () Bool)
(assert edge_a_c)
(assert edge_a_b)
(assert edge_a_e)
(assert edge_b_c)
(assert edge_b_d)
(assert edge_b_e)
(assert (=> edge_a_c (or vertex_a vertex_c)))
(assert (=> edge_a_b (or vertex_a vertex_b)))
(assert (=> edge_a_e (or vertex_a vertex_e)))
(assert (=> edge_b_c (or vertex_b vertex_c)))
(assert (=> edge_b_d (or vertex_b vertex_d)))
(assert (=> edge_b_e (or vertex_b vertex_e)))
(minimize (+ (if vertex_a 1 0) (if vertex_b 1 0) (if vertex_c 1 0) (if vertex_d 1 0) (if vertex_e 1 0)))
(check-sat)
(get-model)
I figured it out (see relevant part below).
No solver is needed but instead an Optimize is used.
The property contains the implications and the the minimize_expr contains the sum over the "true" vertices.
For other examples, I had to also remove the term (if vertex_X 1 0) for unconnected vertices from minimize_expr.
Optimize optimize = context.mkOptimize();
optimize.Add(property);
optimize.MkMinimize(minimize_expr);
optimize.Check();
Model model = optimize.getModel();
Related
If possible I'd like a second opinion on my code.
The constraints of the problem are:
a,b,c,d,e,f are non-zero integers
s1 = [a,b,c] and s2 = [d,e,f] are sets
The sum s1_i + s2_j for i,j = 0..2 has to be a perfect square
I don't understand why but my code returns model not available. Moreover, when commenting out the following lines:
(assert (and (> sqrtx4 1) (= x4 (* sqrtx4 sqrtx4))))
(assert (and (> sqrtx5 1) (= x5 (* sqrtx5 sqrtx5))))
(assert (and (> sqrtx6 1) (= x6 (* sqrtx6 sqrtx6))))
(assert (and (> sqrtx7 1) (= x7 (* sqrtx7 sqrtx7))))
(assert (and (> sqrtx8 1) (= x8 (* sqrtx8 sqrtx8))))
(assert (and (> sqrtx9 1) (= x9 (* sqrtx9 sqrtx9))))
The values for d, e, f are negative. There is no constraint that requires them to do so. I'm wondering if perhaps there are some hidden constraints that sneaked in and mess up the model.
A valid expected solution would be:
a = 3
b = 168
c = 483
d = 1
e = 193
f = 673
Edit: inserting (assert (= a 3)) and (assert (= b 168)) results in the solver finding the correct values. This only puzzles me further.
Full code:
(declare-fun sqrtx1 () Int)
(declare-fun sqrtx2 () Int)
(declare-fun sqrtx3 () Int)
(declare-fun sqrtx4 () Int)
(declare-fun sqrtx5 () Int)
(declare-fun sqrtx6 () Int)
(declare-fun sqrtx7 () Int)
(declare-fun sqrtx8 () Int)
(declare-fun sqrtx9 () Int)
(declare-fun a () Int)
(declare-fun b () Int)
(declare-fun c () Int)
(declare-fun d () Int)
(declare-fun e () Int)
(declare-fun f () Int)
(declare-fun x1 () Int)
(declare-fun x2 () Int)
(declare-fun x3 () Int)
(declare-fun x4 () Int)
(declare-fun x5 () Int)
(declare-fun x6 () Int)
(declare-fun x7 () Int)
(declare-fun x8 () Int)
(declare-fun x9 () Int)
;all numbers are non-zero integers
(assert (not (= a 0)))
(assert (not (= b 0)))
(assert (not (= c 0)))
(assert (not (= d 0)))
(assert (not (= e 0)))
(assert (not (= f 0)))
;both arrays need to be sets
(assert (not (= a b)))
(assert (not (= a c)))
(assert (not (= b c)))
(assert (not (= d e)))
(assert (not (= d f)))
(assert (not (= e f)))
(assert (and (> sqrtx1 1) (= x1 (* sqrtx1 sqrtx1))))
(assert (and (> sqrtx2 1) (= x2 (* sqrtx2 sqrtx2))))
(assert (and (> sqrtx3 1) (= x3 (* sqrtx3 sqrtx3))))
(assert (and (> sqrtx4 1) (= x4 (* sqrtx4 sqrtx4))))
(assert (and (> sqrtx5 1) (= x5 (* sqrtx5 sqrtx5))))
(assert (and (> sqrtx6 1) (= x6 (* sqrtx6 sqrtx6))))
(assert (and (> sqrtx7 1) (= x7 (* sqrtx7 sqrtx7))))
(assert (and (> sqrtx8 1) (= x8 (* sqrtx8 sqrtx8))))
(assert (and (> sqrtx9 1) (= x9 (* sqrtx9 sqrtx9))))
;all combinations of sums need to be squared
(assert (= (+ a d) x1))
(assert (= (+ a e) x2))
(assert (= (+ a f) x3))
(assert (= (+ b d) x4))
(assert (= (+ b e) x5))
(assert (= (+ b f) x6))
(assert (= (+ c d) x7))
(assert (= (+ c e) x8))
(assert (= (+ c f) x9))
(check-sat-using (then simplify solve-eqs smt))
(get-model)
(get-value (a))
(get-value (b))
(get-value (c))
(get-value (d))
(get-value (e))
(get-value (f))
Nonlinear integer arithmetic is undecidable. This means that there is no decision procedure that can decide arbitrary non-linear integer constraints to be satisfiable. This is what z3 is telling you when it says "unknown" as the answer your query.
This, of course, does not mean that individual cases cannot be answered. Z3 has certain tactics it applies to solve such formulas, but it is inherently limited in what it can handle. Your problem falls into that category: One that Z3 is just not capable of solving.
Z3 has a dedicated NRA (non-linear real arithmetic) tactic that you can utilize. It essentially treats all variables as reals, solves the problem (nonlinear real arithmetic is decidable and z3 can find all algebraic real solutions), and then checks if the results are actually integer. If not, it tries another solution over the reals. Sometimes this tactic can handle non-linear integer problems, if you happen to hit the right solution. You can trigger it using:
(check-sat-using qfnra)
Unfortunately it doesn't solve your particular problem in the time I allowed it to run. (More than 10 minutes.) It's unlikely it'll ever hit the right solution.
You really don't have many options here. SMT solvers are just not a good fit for nonlinear integer problems. In fact, as I alluded to above, there is no tool that can handle arbitrary nonlinear integer problems due to undecidability; but some tools fare better than others depending on the algorithms they use.
When you tell z3 what a and b are, you are essentially taking away much of the non-linearity, and the rest becomes easy to handle. It is possible that you can find a sequence of tactics to apply that solves your original, but such tricks are very brittle in practice and not easily discovered; as you are essentially introducing heuristics into the search and you don't have much control over how that behaves.
Side note: Your script can be improved slightly. To express that a bunch of numbers are all different, use the distinct predicate:
(assert (distinct (a b c)))
(assert (distinct (d e f)))
I have the following expression
(declare-fun x00 () Real)
(declare-fun x01 () Real)
(declare-fun x10 () Real)
(declare-fun x11 () Real)
(declare-fun t0init () Real)
(declare-fun z0init0 () Real)
(declare-fun z0init1 () Real)
(assert (>= t0init 0))
(assert (= (+ x00 z0init0) x10))
(assert (= (+ x01 z0init1) x11))
(assert (< (+ (* 1 x00)(* 0 x01)) 0.0))
(assert (= (+ (* 0 x00)(* 1 x01)) 0.0))
(assert (< (+ (* 1 x10)(* 0 x11)) 0.0))
(assert (= (+ (* 0 x10)(* 1 x11)) 0.0))
...
(assert (< (+ (* 1 x40)(* 0 x41)) 0.0))
(assert (= (+ (* 0 x40)(* 1 x41)) 0.0))
(assert (= (+ (* 1 z4end0)(* 0 z4end1)) (* t4end 1)))
(assert (= (+ (* 0 z4end0)(* 1 z4end1)) (* t4end -2)))
and I would like to express as a simple formula in order to express the following:
(assert exists (x00 x01) ("the above expression"))
and then perform a quantifier elimination.
Is there anyone who knows how to proceed?
I know how to do it with z3py but I need some faster solution.
Thank you very much for any hint.
One possible solution is as follows
(declare-fun x00 () Real)
(declare-fun x01 () Real)
(declare-fun x10 () Real)
(declare-fun x11 () Real)
(declare-fun t0init () Real)
(declare-fun z0init0 () Real)
(declare-fun z0init1 () Real)
(define-fun conjecture () Bool
(and (>= t0init 0) (= (+ x00 z0init0) x10) (= (+ x01 z0init1) x11)))
(assert (exists ((x00 Real) (x01 Real)) conjecture))
(check-sat)
and the corresponding output is
sat
I am not sure if the quantifier elimination that you need will work with Z3. Maybe for your problem "Redlog" of "Reduce" is the better option. All the best.
The following SMT-LIB code runs without problems in Z3, MathSat and CVC4 but it is not running in Alt-Ergo, please let me know what happens, many thanks:
(set-logic QF_UF)
(set-option :incremental true)
(set-option :produce-models true)
(declare-fun m () Bool)
(declare-fun p () Bool)
(declare-fun b () Bool)
(declare-fun c () Bool)
(declare-fun r () Bool)
(declare-fun al () Bool)
(declare-fun all () Bool)
(declare-fun la () Bool)
(declare-fun lal () Bool)
(declare-fun g () Bool)
(declare-fun a () Bool)
(define-fun conjecture () Bool
(and (= (and (not r) c) m) (= p m) (= b m) (= c (not g))
(= (and (not al) (not all)) r) (= (and la b) al)
(= (or al la lal) all) (= (and (not g) p a) la)
(= (and (not g) (or la a)) lal)))
(push 1)
(assert (and conjecture (= a false) (= g false)))
(check-sat)
(get-model)
(pop 1)
(push 1)
(assert (and conjecture (= a false) (= g true)))
(check-sat)
(get-model)
(pop 1)
(push 1)
(assert (and conjecture (= a true) (= g true)))
(check-sat)
(get-model)
(pop 1)
(push 1)
(assert (and conjecture (= a true) (= g false)))
(check-sat)
(get-model)
For now, Alt-Ergo does not provide a full support for the SMT-2 format. In particular, the command get-model is not recognized.
Moreover, the commands push and pop are ignored. This is why Alt-Ergo says sat, unsat, ..., unsat on the given code (when get-model is removed).
Is there any way to apply simplifications to uninterpreted functions defined in z3, rather than the goals and subgoals ?
I have the following z3 code :
(declare-fun f (Bool Bool) Bool)
(assert (forall ((b1 Bool) (b2 Bool))
(implies b2 (f b1 b2))))
(assert (exists ((b1 Bool) (b2 Bool))
(not (f b1 b2))))
(check-sat)
(get-model)
And I get the following output:
sat
(model
(define-fun b1!1 () Bool
false)
(define-fun b2!0 () Bool
false)
(define-fun k!7 ((x!1 Bool)) Bool
false)
(define-fun f!8 ((x!1 Bool) (x!2 Bool)) Bool
(ite (and (= x!1 false) (= x!2 true)) true
false))
(define-fun k!6 ((x!1 Bool)) Bool
(ite (= x!1 false) false
true))
(define-fun f ((x!1 Bool) (x!2 Bool)) Bool
(f!8 (k!7 x!1) (k!6 x!2)))
)
It turns out that by applying rewrite rules to the definition of f, we can get that
f is equal to the second argument (x!2) by the following derivation:
(f!8 (k!7 x!1) (k!6 x!2))
= (f!8 false (k!6 x!2))
= (f!8 false x!2)
=(x!2)
Is there any way to get z3 to produce the following definition automatically ?
(define-fun f ((x!1 Bool) (x!2 Bool)) Bool
(x!2))
Thanks for your help.
Regards,
Oswaldo.
One option is to ask Z3 to evaluate the expression (f x y) where x and y are fresh Boolean constants. The eval command will evaluated (f x y) in the current model, and will produce y in your example. Here is the complete example (also available online here):
(declare-fun f (Bool Bool) Bool)
; x and y are free Boolean constants that will be used to create the expression (f x y)
(declare-const x Bool)
(declare-const y Bool)
(assert (forall ((b1 Bool) (b2 Bool))
(implies b2 (f b1 b2))))
(assert (exists ((b1 Bool) (b2 Bool))
(not (f b1 b2))))
(check-sat)
(eval (f x y))
I've the following SMT-Lib2 script:
(set-option :produce-models true)
(declare-fun s0 () Int)
(declare-fun table0 (Int) (_ BitVec 8))
(assert (= (table0 0) #x00))
(assert
(let ((s3 (ite (or (< s0 0) (<= 1 s0)) #x01 (table0 s0))))
(let ((s5 (ite (bvuge s3 #x02) #b1 #b0)))
(= s5 #b1))))
(check-sat)
(get-model)
With Z3 v3.2 running on the Mac, I get:
sat
(model
;; universe for (_ BitVec 8):
;; bv!val!2 bv!val!3 bv!val!0 bv!val!1
;; -----------
;; definitions for universe elements:
(declare-fun bv!val!2 () (_ BitVec 8))
(declare-fun bv!val!3 () (_ BitVec 8))
(declare-fun bv!val!0 () (_ BitVec 8))
(declare-fun bv!val!1 () (_ BitVec 8))
;; cardinality constraint:
(forall ((x (_ BitVec 8)))
(and (= x bv!val!2) (= x bv!val!3) (= x bv!val!0) (= x bv!val!1)))
;; -----------
(define-fun s0 () Int
(- 1))
(define-fun table0 ((x!1 Int)) (_ BitVec 8)
(ite (= x!1 0) bv!val!0
(ite (= x!1 (- 1)) bv!val!3
bv!val!0)))
)
Which states that s0 = -1 is a model. However, with s0 = -1, we have s3 = 1 and s5 = #b0, which makes the assertion false. In fact, I'm quite sure the benchmark as stated is unsatisfiable.
One thing I noticed in the Z3 output is the quantified formula it gives for the cardinality constraint. It says:
;; cardinality constraint:
(forall ((x (_ BitVec 8)))
(and (= x bv!val!2) (= x bv!val!3) (= x bv!val!0) (= x bv!val!1)))
The assertion is a conjunction, which sounds rather weird; shouldn't that be a disjunction? I'm not sure if this is the root-cause of the problem, but it sure sounds fishy.
There are two problems in Z3.
First, you are correct, there is a typo in the model printer. It should be a "or" instead of an "and". The second problem is that Z3 did not install the bit-vector theory and treated (_ BitVec 8) as a uninterpreted sort. This was a bug in the preprocessor that is used to decide in which logic the problem is in. You can workaround this bug by adding the following command in the beginning of the file:
(set-option :auto-config false)
These bugs have been fixed, and the fix will be available in the next release.