I am using Z3 to solve a problem and I find it is very slow.
Are there any general principles or guidelines about the acceleration of Z3 solver? Such as:
Try to reduce the number of constraints.
Try specifying the tactics.
...
There are no generally applicable rules; otherwise we would have implemented and automated them. Without further information about the problem, there is no way to help you. A good place for performance investigations is a Z3 GitHub discussion.
As Christoph mentioned, there's no "one-size-fits-all" advice that applies uniformly to all problems. However, this sort of performance question comes up often enough, and there has been previous discussion on stack-overflow with a summary of how to think about scalability before: Scalability of z3
I'd start by reviewing this answer, and see if you have specific questions. In particular, sharing the particulars of your actual problem and how you modeled it in z3 will be essential to get better guidance.
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I am doing a project at the university and I need to train an algorithm to rephrase sentences, what can you advise for implementation? Is it possible to use a translator to translate into another language in the end to get a paraphrased sentence? Also i want to use Word2Vec, or it's a bad idea?
This kind of broad-advice question – and about a very-tough problem, paraphrasing text, that is still a very active research problem – would be better answered by surveyin the research literature.
A great site for searching relevant papers – and then finding other related papers once you've set some positive examples – is http://www.arxiv-sanity.com/.
Searching for [paraphrasing] or [summarization] would give you a running start in seeing major techniques & their limitations. And, once you start bookmarking papers by the little 'disk' icon, it can autosuggest important related papers... so even if your 1st few finds are tangential or far-from-usefulness, it can lead you to the seminal papers, & prevailing cutting-edge algorithms/libraries, pretty quickly.
Currently, I have a somewhat superficial understanding of how SMT solvers work (the basics of algorithms like E-matching, MBQI, and CVC4/5's inductive reasoning). However, it's very frustrating to debug by trial-and-error.
Is there any guidance on how to debug SMT scripts that make heavy use of quantifiers?
A badly-written script often goes into infinite loop but I cannot tell if it's my mistake, or it's just taking too long to respond.
The SMT solvers tend to hide internals from users, so it's quite hard to figure out why it's stuck. Is there any way to print the "solving context"?
Or maybe I'm using SMT solvers the wrong way? I should design my own verification algorithm, only employing SMT solvers for local decisions?
Any help is appreciated!
This is a very subjective question, and largely opinion based. But a couple of general remarks:
Don't directly program in SMTLib. It is not meant to be for human-consumption. Instead, use a higher-level API, and script them from a language that you're more familiar with. There are bindings available from any number of languages, including C/C++/Java/Python/O'Caml/Haskell/Scala etc. Just doing this will get rid of most of the mundane mistakes you make.
Turn on verbosity output of the solver. You might be able to notice patterns in the log output. Unfortunately this is very solver specific, and can be hard to decipher; but can also indicate if, for instance, you're stuck in an e-matching loop in the presence of quantifiers.
If there's a custom algorithm for your verification problem (Hoare triples, separation logic, abstract interpretation, ...), then you first have to apply these techniques and delegate local/sub-lemmas to an SMT solver. Do not expect the SMT solver to be able to do large proofs, and anything that requires actual induction out-of-the box.
Try reducing complexity by putting in over-constraints and see which ones help. Based on your findings you might be able to do a case-split, for instance, if the over-constraints enumerate a reasonably small search-space.
Again, these are very general remarks and whether they'll apply for your specific problem is anyone's guess. But I'd start with coding in a higher-level API if you aren't already doing so.
I have downloaded z3 and find a mini_ic3.py program? I think it is for ic3--an inductive invariant -based formal verification program.
is there some reference paper to recommend for understanding mini_ic3.py in z3 directory
Not much directly describing that particular implementation, I'm afraid. Your best bet is to read through https://theory.stanford.edu/~nikolaj/programmingz3.html#sec-bounded-model-checking
The original IC3 papers themselves would help as well. The following is a great introduction: http://theory.stanford.edu/~arbrad/papers/Understanding_IC3.pdf
I am trying to Code a genetic algorithm in Matlab but really dont know how it works in images and how to proceed? Is there any basic tutorial that can help me understand how to apply GA on images (starting from 2d to multidimentional images ).
That will be a great help for me.
Thanking everyone in anticipations.
Kind Regards.
For GA you need two things: a fitness function that can evaluate any solution and tell how good it is, and a representation of your solution so that you can do crossover and mutation. Once you have these, you are good to go. I'm not an expert on image processing so I can't help you with that exactly.
Look at the book Essentials of metaheuristics which is a very good resource for start with evolutionary computation (and not only that) in general. It's free.
There is a paper on this subject which you can find at the IEEE library. I believe it solves the problem you vaguely describe.
The problem statement is kind of vague but i am looking for directions because of privacy policy i can't share exact details. so please help out.
We have a problem at hand where we need to increase the efficiency of equipment or in other words decide on which values across multiple parameters should the machines operate to produce optimal outputs.
My query is whether it is possible to come up with such numbers using Linear Regression or Multinomial Logistic Regression algorithms, if no then can you please specify which algorithms will be more suitable. Also can you please point me to some active research done on this kind of problem that is available in public domain.
Does the type of problem i am asking suggestions for comes in the area of Machine Learning ?
Lots of unknowns here but I’ll make some assumptions.
What you are attempting to do could probably be achieved with multiple linear regression. I have zero familiarity with the Amazon service (I didn’t even know it existed until you brought this up, it’s not available in Europe). However, a read of the documentation suggests that the Amazon service would be capable of doing this for you. The problem you will perhaps have is that it’s geared to people unfamiliar with this field and a lot of its functionality might be removed or clumped together to prevent confusion. I am under the impression that you have turned to this service because you too are somewhat unfamiliar with this field.
Something that may suit your needs better is Response Surface Methodology (RSM), which I have applied to industrial optimisation problems that I think are similar to what you suggest. RSM works best if you can obtain your data through an experimental design such as a Central Composite Design or Box-Behnken design. I suggest you spend some time Googling these terms to get your head around them, I don’t think it’s an unmanageable burden to learn how to apply these with no prior experience in this area. Because your question is vague, only you can determine if this really is suitable. If you already have the data in an unstructured format, you can still generate an RSM but it is less robust. There are plenty of open-access articles using these techniques but Science Direct is conveniently down at the moment!
Minitab is a software package that will do all the regression and RSM for you. Its strength is that it has a robust GUI and partially reflects Excel so it is far less daunting to get into than something like R. It also has plenty of guides online. They offer a 30 day free trial so it might be worth doing some background reading, collecting the tutorials you need and develop a plan of action before downloading the trial.
Hope that is some help.