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Man, lately, I feel like this stuff has been following me around. I'd really like to deep-dive into logic programming and related paradigms. Just recently came across Answer Set Programming[0] (via Potassco's clingo[1]), and it has made me realize just how ignorant I am of the design space that's being explored here. More personally, I recently spent enough time with first Scheme and then APL that the paradigms click…
It makes the same analogy that Prolog (or logic programming languages in general) have been strongly influenced by the resolution algorithm. In practice that means that if you write a non-trivial program, if performance is not right you'll need to understand the execution model and adapt to it, mainly with the pruning operator (!). So while the promise is to "declare" values and not think about the implementation details, you're railroaded to think in a very specific way.
I personally found that frustrating to find good solutions essentially unworkable because of this, in comparison with either imperative or functional paradigms that are significantly more flexible. As a result, Prolog-style programming feels limited to the small problems for which it is readily a good fit, to be integrated into a general program using a general-purpose language. I may be wrong on this, but of the 50 people that learned Prolog around the same time as me, none kept up with it. Meanwhile, other niche languages like Ocaml, Haskell and Scheme had good success.
Rethinking the language foundation could remove these barriers to give the language a broader user base.
Man, lately, I feel like this stuff has been following me around. I'd really like to deep-dive into logic programming and related paradigms. Just recently came across Answer Set Programming[0] (via Potassco's clingo[1]), and it has made me realize just how ignorant I am of the design space that's being explored here. More personally, I recently spent enough time with first Scheme and then APL that the paradigms click…
Abstract . Logic programming has a long history. The representative of logic programming in practice, the language Prolog, has been introduced more than 50 years ago. The main features of Prolog are still present today: a Prolog program is a set of predicate definitions executed by resolution steps with a backtracking search strategy. The use of back- tracking was justified by efficiency reasons when Prolog was inven…
I didn't read past the abstract, but it sounds like they are just transforming logic-based programs into function-based programs. But: if I wanted functional programming, I wouldn't be writing in Prolog. What would be interesting, would be to replace depth-first search while remaining in the world of predicates and Horn clauses.
I say naïvely because on one hand you might not need all versions of the function, but on the other one you can also provide partial values, so it’s not either input or output.
Abstract . Logic programming has a long history. The representative of logic programming in practice, the language Prolog, has been introduced more than 50 years ago. The main features of Prolog are still present today: a Prolog program is a set of predicate definitions executed by resolution steps with a backtracking search strategy. The use of back- tracking was justified by efficiency reasons when Prolog was inven…
isn't backtracking a complete search strategy?
Backtracking is a complete search of the problem-space.
What is incomplete is the Horn-SAT problem space, which is a subset of SAT, that can be solved in polynomial time, and is what Prolog is based on.
A complete logic system would have to solve SAT, which is NP-complete.
At least that's what I understood they meant by that.
See: - The fastest non-incremental embedded Datalog engine https://github.com/s-arash/ascent - The state-of-the-art non-embedded and non-incremental Datalog engine https://github.com/knowsys/nemo - A python library that contains an embedded incremental Datalog engine https://github.com/brurucy/pydbsp - A Rust library that provides a embedded incremental Datalog engine over property graphs https://github.com/brurucy/materialized-view
Datalog does not use backtracking, and is getting ever increasingly more popular. See: - The fastest non-incremental embedded Datalog engine https://github.com/s-arash/ascent - The state-of-the-art non-embedded and non-incremental Datalog engine https://github.com/knowsys/nemo - A python library that contains an embedded incremental Datalog engine https://github.com/brurucy/pydbsp - A Rust library that provides a emb…