clpz
csips
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| clpz | csips | |
|---|---|---|
| 5 | 1 | |
| 172 | 1 | |
| - | - | |
| 4.4 | 0.0 | |
| 3 months ago | about 2 years ago | |
| Prolog | Python | |
| - | GNU General Public License v3.0 only |
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clpz
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Logic programming is overrated, at least for logic puzzles (2013)
As pointed out in the comments in the article, these kinds of logic puzzles are easier to solve using constraint programming than "regular" logic programming.
For example, see the solution to the Zebra Puzzle here: https://www.metalevel.at/prolog/puzzles which uses CLPZ[^1].
[^1]: https://github.com/triska/clpz
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Markus Triska Interview on Prolog
Scryer has the strings-as-lists-but-implemented-efficiently thing, possibly more strict ISO Prolog compatible syntax, and it may ship with a more advanced constraint library (I'm not clear on the relationship between SWI's clpfd and Scryer clpz).
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is it possible to have a reversable operation
None of these are full-fledged programming languages, however. They're limited to problems that lie in the polynomial hierarchy (A class which contains P and NP). Logic programming is generally only used to solve hard problems for which no good algorithm is known. Prolog also sort of fits this niche and it has a bunch of solvers integrated into it. Notably CLPFD which uses https://github.com/triska/clpz for constraint logic programming. Rosette (https://docs.racket-lang.org/rosette-guide/index.html) is another solver-based language. Except it uses lisp syntax (it's embedded in the Racket language). It uses Z3 as a solver (linked above for SMT theories)
- Ask HN: Do you use an optimization solver? Which one? Why? Do you like it?
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What is the difference between constraint solving and constraints programming?
Constraint programming I guess is when one uses a prolog library such as: https://github.com/triska/clpz
csips
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Ask HN: Do you use an optimization solver? Which one? Why? Do you like it?
I actually just finished implementing an extremely simple Integer Linear Program solver in Python as an educational exercise, wrapping scipy's linprog function to solve the linear relaxation. It has an expression syntax so you don't have to specify the matrix and vectors for the standard form, and it does branch-and-cut on the linear relaxation
https://github.com/cwpearson/csips
What are some alternatives?
prolog-checkers - A Player vs AI game of checkers implemented in Prolog
HiGHS - Linear optimization software
HybridTSPSolver - A hybrid TSP solver that I made for my master's degree thesis in computer science.
SSI - A Prolog Compiler written in Prolog.
osqp - The Operator Splitting QP Solver
kanren - An extensible, lightweight relational/logic programming DSL written in pure Python
exact
or-tools - Google's Operations Research tools:
golomb-solver - Create Golomb rulers with constraint programming
optaplanner-quickstarts - Mirror of https://github.com/apache/incubator-kie-optaplanner-quickstarts