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169 pointsprofquail72 comments

I would be really interesting in getting a list of common problem or category of problem that people usually implement in "common" languages but that would benefit highly from being written using Prolog.

I did learn prolog during my engineer degree but we never went further than the "school" exercises of finding if Mary is a member of the family of Bob or not.

I then later played, while still being a student (i.e still playing with things for intellectual fun rather than actual real life/business problem solving) a bit with Flora2 http://flora.sourceforge.net/ that seams to me like a hackier but stronger variant of Prolog (the object-like syntax and the possibility to pass rule has parameter to other rule).

At the opposite I learned also about functional programming, and until last year I was also wondering the same until it became clear to me with javascript (for the 'no class', function as parameter) and Rust (for the immutable by default part). Ohhhhh suddenly all these for loop to create an other list of the same size, all these for loop to arrive to one result, all these for loop to get a subset of the list, all these for loop to find one specific value, ALL gones and replaced by primitives.

All of that to say I really hope I'm missing something with Prolog that can elevate my thinking.

I could think of some interesting applications for graph analysis and the semantic web with Prolog. As an outsider looking in, Prolog as a programming language appears to have a lot more flexibility than a query language such as SPARQL or the various graph traversal libraries and APIs that are out there.

Authorization is a good fit - express your groups and roles as facts and rules (primitives) and then queries are... queries.

I suggest looking at the SWI-Prolog web site for a variety of Prolog applications and addons.

A lot of UI programming patterns are much easier to express in a constraint programming language. Things like data binding don't exist in logic programming, since they are captured by constraints. It is also easier to do common tasks like position elements in a way which reacts nicely due to resizing a viewport, etc.

Today constraint solving is still confined to a lot of niche applications like physics engines or CAD systems, but I keep hoping for the day that someone will build a more integrated system which makes it easier for anyone to grab constraints and plug them in where it makes sense.

Autolayout (iOS and OS X layout engine) is built on a constraint solver.

Prolog isn't a numerical constraint solver.

I once had to write a menu system in Turbo Prolog. Not fun. Totally the wrong tool for the job. Prolog isn't that useful when you have to cause an action, as opposed to computing a result.

Have you used any of the numerical constraint solving libraries available for many Prolog implementations?[1] (It is also worth noting that Turbo Prolog is a rather peculiar—and now rather old—take on Prolog. I believe it has been superseded by Visual Prolog).

[1]: e.g., SWI Prolog's http://www.swi-prolog.org/pldoc/man?section=clpfd, or http://www.swi-prolog.org/pldoc/man?section=clpqr

Another issue for prolog is that many of these "constraint solving" problems will lead to exponential-time algorithms in the worst case, specially if you use a naive implementation. Because of this, its common to use more specialized solvers (linear programming, SAT, ILP, SMT, etc) instead of a general logic-programming one.

Here's an interesting example of a problem with a logic programming technique:

http://ir.lib.uwo.ca/cgi/viewcontent.cgi?article=2646&contex...

If my link epic fails its "Representing Game Dialogue as Expressions in First-Order Logic" by Kaylen FJ Wheeler

Something like using clojure core.logic which is a minikanen which is prolog to implement video game dialogue programatically. Its a one line summary of 100 pages so take with grain of salt.

I have no connection with this topic other than skimming the paper when I went thru a phase after reading the most recent 7 languages in 7 weeks book and googling for minikanren applications and generally fooling around with the topic. There may or may not be better example, but it is at least "an" example.

NLP is old territory for AI and lisp and the like. Whats interesting about this specific part of NLP is limiting the territory and "guiding" it to fit a gaming requirement and integrating the conversation with game plot, more or less.

As another example, I thought for a bit about some kind of prolog reasoning engine to help with some ETL stuff I do and got pretty much nowhere, although it also is a limited area of NLP type stuff. There probably is some way to apply it... somehow. There should be a way to semi-intelligently read engineering data formatted in vague and confusing ways then reason about how to correctly import it.

At university Datalog and Prolog worked great for sample tasks. But I always wondered if Prolog scales to real world tasks.

I think it depends on one's notion of "scale". Expert systems would typically have few, correct facts. Or put another way, little, but very accurate information. If you say that anything less than a 128 (or 64 or 32 for that matter) gb working set is "small" (fits in ram) - for many problems you never need to "scale".

I don't have a list, but I once wrote a software for finding the weak keys on Triple-DES using a functional-logic language. Writing the software was mostly defining the problem in a mathematical way, on the left side defining the hashing function and on the right side defining the desired properties (same output), leaving the hashes as free variables.

I have to say I was not only amazed by the exact solutions provided, but that it was found in 12 milliseconds - which includes program load and I/O time.

There's no simple list, really...it's just highly domain specific. I can give you an example though.

At work, we have a very large set of data representing individual "runs" that has to be "scored" (given various different numbers) in an ever-growing list of complicated ways. Originally these scorers were written in Python. This proved to be very difficult to maintain, and we recently moved to writing these in a Prolog-like language (not Prolog, but close enough for this discussion). At the end of the day it feels kind of like a much more powerful SQL (which makes sense, as SQL is a "relational" programming language and quite similar in concept). The facilities of logic programming perfectly fits this use case.

Similarly, you might take a look at anything people use "miniKanren" (an embeddable logic DSL) for. The fundamental thing to realize about Prolog, imho, is that while it's Turing-complete and has GUI facilities I wouldn't really call it a general-purpose programming language. It really works best as something like a DSL when you have tasks that require lots of logic and searching.

edit: Actually, writing this, I have a list for you. Do you need to perform a search and compute a result over a big data set, sort of like (in theory) you would with SQL on a relational DB? Then that's where logic programming languages shine.

Both GNU and SWI Prolog have bi-directional C interfaces. Prolog can be used as a mini-language under C, at least with those implementations.

I had a ton of fun with Prolog embedded in the Tivoli Enterprise Console for managing network events from OpenView/NetView and a gaggle of other tools in a huge network.

We basically took about 120k daily events and turned that into about 60 actionable events that were meaningful to the NOC... All in about 2,000 LoC.

When our was at university, for part of the computer algebra course we had to work with a MacOS theorem prover application, written totally in house.

The theorem prover logic was in Prolog: it was totally the right tool for the job, and was small, effective, usable and (relatively) easy to understand.

The MacOS user interface was also in Prolog: it was totally not the right tool for the job, and to this day I am still astonished that it could even be done, let alone produce a usable UI.

FWIW, I found it interesting to learn that the Soviet Space shuttle (Buran) was programmed in Prolog.

http://programmers.stackexchange.com/questions/145669/what-s...

http://en.wikipedia.org/wiki/Buran_(spacecraft)#Overview

I think this might be a misunderstanding, the claim just shows up in a single CIA report about contemporary Soviet computer technology. Elsewhere[0] we read,

> Two new specific software languages known as "PROL-2" (used by the on-board computers) and "DIPOL" (used by ground computers using vehicle testing) [...] were developed for Buran

So I guess the what the CIA report refers to as Prolog is PROL-2. But is this really a Prolog variant? That seems like an unlikely choice of language for a real-time system.

Later, both of these languages developed into DRAKON [1], and looking at the Wikipedia page that language doesn't appear very Prolog-like, at least not superficially.

On the other hand, here[2] is a reddit comment that claims that is was indeed a Prolog variant, but it doesn't cite the source.

[0] https://books.google.com/books?id=qSwNBwAAQBAJ&pg=PT6&lpg=PT...

[1] https://en.wikipedia.org/wiki/DRAKON

[2] http://www.reddit.com/r/programming/comments/ujx7m/what_soft...

After my post I read up more and, like you, am now skeptical. I wonder if it's a case of someone mistaking PROL to be an abbreviation of prolog?

My old German university's web server was written in prolog, so it's not completeley inconceivable for a spacecraft, but I'd like to see more evidence.

Yes, that is my guess too. On the other hand, I would be _extremely_ interested to see a real-time Prolog dialect used to control real-life space shuttles, that's totally my aesthetic. :) But I can't understand Russian, which makes it difficult to research.

I've been actively trying to learn Prolog for the past few months. It's definitely very different from other languages I've used, and it's changed the way I think about programming. Prolog seems to be a really brilliant set of ideas embedded inside a mediocre syntax with poor library support for things that are trivially easy in other languages.

I think Prolog rules can replace a lot of spaghetti code: stuff like "Usually do this, but then other times do this, unless this other thing is true. If there's a parse error, then do xyz and keep going." In ordinary procedural code, the exception cases can dominate the body of a function and may need to be deeply nested, but in Prolog, it's possible to cordon them off or express them at the top level.

I suspect it might be most useful as a DSL you can embed inside of other languages, though I haven't seen a good implementation of that. (The clojure core.logic library mentioned elsewhere looks really promising.)

I think it may also be useful for domain experts to specify simple rules that capture an aspect of their expertise. If you restrict the domain down enough, and work to figure out what predicates are needed, prolog rules can become easy enough to read that you don't need to know much programming to use them. But the devil seems to be in the details of connecting the core logic into a bigger system that actually does something.

For example, the answer for hooking prolog up to a SQL database is "Look at the ODBC library!", which is not a very satisfactory answer. I think you could build a really beautiful ORM system in Prolog, but nobody's done it yet. (Maybe ORM isn't the right phrase, but a clean way of relating prolog queries to database queries and vice versa.)

The syntax is wonderfully simple, but also has almost no sugar for common idioms. The predicate notation makes it somewhat harder to batch up a bunch of attributes into one conceptual "thing" than in other languages. That means you need to keep positional arguments in your head a lot more. I think aping the class constructor and attribute notation of other languages would be helpful like `my_foo(foo, bar:attr, baz:attr) :- [...].` Then you could reference that either as a constructor (`my_foo(a,b,c)` would state that `a.bar=b` and `a.baz=c`) or to generate goals, like `my_foo(foo), other_predicate(foo.bar)`. Prolog is so old that choices like "make '.' the end of a statement" made sense at the time, but haven't stood the test of history.

(Disclaimer: Many of my criticisms may have perfectly valid solutions in prolog. I'm still learning it.)

This exists. It is called Datalog.

Datalog is a query language, but I haven't found good libraries for the "connector" pieces of translating prolog/datalog predicates to SQL, constructing or syncing schema definitions, and database migrations. It seems like if you want to use Datalog, Datomic is the best option. (But datomic is sort of pricey for commercial use relative to SQL databases like Postgresql.)

"Usually do this, but then other times do this, unless this other thing is true. If there's a parse error, then do xyz and keep going."

This is almost exactly like the descriptions I get from my team leader for getting results out of a database. He doesn't think in sets for SQL.

Right. I think this is how a lot of business requirements are specified, since they are frequently constructed by non-programmers. Taking a bunch of cases from a spec document generated by a domain expert and turning them into maintainable/readable procedural code takes a lot of creativity. I think it's easier to express case analysis like this in Prolog.

What sort of library support have you found wanting? While the Prolog ecosystem is admittedly tiny compared to mainstream languages, I have often been surprised by the amount of useful libraries available.

I love Prolog syntax. I do think there is room for improvement, but the language is also extremely flexible, and it is very easy to roll your own syntax. Funny enough, so far my many experiments with alternative syntax have mainly had the effect of convincing me of the elegance and power of standard Prolog syntax.

While there is no particular reason the '.' should be used to terminate statements (except the resonance with many natural languages in this regard), I think some sort of terminator is necessary to keep the syntax as flexible as possible. Like Lisp, Prolog syntax is isomorphic to its AST. Currently my main gripe with Prolog syntax is that it represents conjunction and delimitation of predicate arguments and list items with the same operator, `(,)/2`. However, that can be fixed in two lines:

    :- op(1000, xfy, user:(&)).
    A & B :- A, B.

But I'm not sure it really needs "fixing"...

Regarding, "batching up a bunch of attributes into one conceptual 'thing'": SWI-Prolog has implemented a special data structure it calls "dicts"[dicts] for this purpose, but I am not very fond of it (and there's a fair amount of concern over the way this implementation breaks compatibility with ISO standards). More traditional solutions are to use lists of "pairs"[pairs], option lists[option], or, for larger data structures and when performance and lookup time is an issue, association lists[assoc] or records[records]. Using the first of these techniques looks like this:

    my_foo(a, [bar-Bar, baz-Baz]) :-
        Bar = something,
        Baz = something_else.
    
    get_attr(Pairs, Key-Value) :-
        member(Key-Value, Pairs).
    set_attr(Pairs, Key-Value, NewPairs) :-
        ( select(Key-_, Pairs, Key-Value, NewPairs), !
        ; NewPairs = [Key-Value|Pairs]
        ).

    ?- my_foo(a, As), get_attr(As, baz-X), writeln(X), set_attr(As, boz-another_thing, Bs), writeln(Bs).
    something_else
    [boz-another_thing,bar-something,baz-something_else]
    As = [bar-something, baz-something_else],
    X = something_else,
    Bs = [boz-another_thing, bar-something, baz-something_else].

It might be the case that Prolog's flexible syntax leaves it spoiled for choices here... That being said, it would be straightforward to implement syntax similar to your description, which evaluates and replace attribute accessors in place, using `term_expansion/2` and `goal_expansion/2`. Then you could use `As.baz` in place of the value itself (I've done so before, and this is what the SWI-Prolog's dict expansion does). Even easier, you could use Michael Hendricks' func package[func] to make a function for this purpose. But I've increasingly come to think of Prolog's explicit evaluation as a unique strength rather than a problem to be solved.

[dicts]: http://www.swi-prolog.org/pldoc/man?section=dicts

[pairs]: http://www.swi-prolog.org/pldoc/man?section=pairs

[option]: http://www.swi-prolog.org/pldoc/man?section=option

[records]: http://www.swi-prolog.org/pldoc/man?section=record

[func]: http://www.swi-prolog.org/pack/list?p=func

I definitely agree that the terminator is a good idea, just that "." happened to be an unfortunately historical choice since other languages used that character for a very different meaning.

Thanks for the links! These look extremely helpful!

Am in my daipers. Could you point me in the right direction in learning about querying prolog through JavaScript. Av read some documentation on Pengines but wud love some more example code.

Nokia N9* handsets run prolog code

http://www.reddit.com/r/programming/comments/ijxdl/nokias_n9...

Logic programming shines in any domain where unification is used heavily. An example is writing executable semantics or type inference/checking algorithms. Here's some code I hacked up as an example a few years ago that implements an interpreter and HM type inference for a small functional language: http://pastebin.com/aWBWSwiW

Part of the question parser in the Jeopardy version of IBM Watson uses Prolog[1]. There's a lot more to it than that single part though.

[1] http://www.cs.nmsu.edu/ALP/2011/03/natural-language-processi...

You might be interested in these SO answers regarding "Real world Prolog Usage": http://stackoverflow.com/questions/130097/real-world-prolog-... The answers are replete with claims about good use-cases for Prolog.

Michael Hendricks' talk at last year's Strange Loop on "Production Prolog" gives an excellent high-level survey of the uses, advantages, and drawbacks of Prolog: https://www.youtube.com/watch?v=G_eYTctGZw8

BTW, I have played a tiny bit with Flora2 myself. It seemed really neat. If you're interested in the intersection of OO and Prolog, you may also want to look at Logtalk[0]. FWIW, if I understand your meaning correctly, it is very easy to "pass rules as parameters to other rules" in vanilla Prolog. It facilitates all sorts of higher-order approaches and is very good for meta-programming.

[0]:http://logtalk.org/

Gerrit, a Git server with code review, lets users write custom submit-rules with Prolog: https://gerrit-review.googlesource.com/Documentation/prolog-...

Shawn Pearce, the author of Gerrit, explains why he thinks Prolog is well suited for this: https://groups.google.com/forum/#!msg/repo-discuss/wJxTGhlHZ...

I've used it as the basis for a rules based heads up no limit poker agent (game logic is also implemented in Prolog, GUI is Java/JS...needs a major rewrite though). Constraint satisfaction programming is pretty helpful.

It's mostly a rather simple agent but I'm currently working on a DSL to codify strategies more easily. I'm fully aware a rules based agent will never be strong but I'm mostly interested in figuring out how well experts can codify their strategies and if you can make them comparable (also looking into inductive reasoning and datamining strategy rules from sufficient hand samples of winning online players)

Mostly a toy project these days :)

[Edit: I'm actually going to rewrite it because it used Sicstus and I want to use an open implementation so I'll switch to SWI + while I'm at it I'll drop the Java stuff and go full JS/HTML. Pengines looks pretty good: http://www.swi-prolog.org/pldoc/package/pengines.html]

All standard Prolog really does is matching up "trees with wildcards in them" with other "trees with wildcards in them". The matching process happens in a very specific order and all I/O happens as side effects of small steps in the matching process (I/O operations are implemented as pseudo-constraints, i.e. small "twigs").

As a result, the order you write your constraints ("trees") in in Prolog is /very/ important. Things may not terminate or may blow up the stack or take far, far too long or produce the wrong I/O if the order isn't just right.

So standard Prolog is not a nice language.

But the idea of specifying constraints and let the computer find solutions is really nice. If only we didn't have those side effects weaved into the constraint solving process. And if we could specify the constraints separately from heuristics on how to solve them (i.e. the order in which to try things). Or if it could handle something more interesting than just "trees with wildcards".

mini-Kanren seems to be such a better constraint solving language -- I haven't tried it yet, since I am not done with my Prolog studies but I'm very much looking forward to it.

Some Prologs have extensions that ameliorate or completely fix some of the problems with Prologs. GNU Prolog, for example, has an extension to handle other kinds of finite domains (such as integers) than just trees:

http://www.gprolog.org/manual/html_node/gprolog055.html

I think the same guy who wrote that code also has a nice paper on how to extend it (efficiently!) to floating-point variables.

Not even a full Prolog, but Datalog, is very well suited for querying about graphs. I.e., for quite a lot of things you want to do inside a compiler. See an example here: http://people.csail.mit.edu/mcarbin/papers/aplas05.pdf

I also use full Prolog to implement type systems.

Prolog extended with a constraint solver is another thing one may want to employ for an elaborate program analysis, see how https://github.com/eholk/harlan is using cKanren for its region inference.

So, in my book, Prolog per se may have very limited use outside of teaching, but an embedded Prolog or a dumbed down Datalog can be an extremely powerful querying DSL which can make LINQ look dumb and clumsy.

Agreed. I think this thought was the starting point of the http://cascalog.org/ project (a high level clojure frontend for Hadoop MapReduce).

We use it a lot - we receive requests of up to 5 M size of .Net structures, and just wade through all the strange class-relations with Prolog :)

I read that in 2014, 1/3 of all flight bookings in the word went through (Sicstus) Prolog.

It has its uses, and I like working in it :)

Configuration problems -- "I'd like the fizzbiggle thingy with quanger III options and a blue prelz in red. Will that fit through my door and how much will it cost?".

http://en.wikipedia.org/wiki/Xcon

http://cri-dist.univ-paris1.fr/diaz/publications/PL/rcis11.p...

http://cri-dist.univ-paris1.fr/diaz/publications/PL/rsse14.p...

It's cool to see this, but I think what Prolog could really use is a "Real World Prolog" style of treatment showing things outside the usual logic puzzles and toy genealogy examples. Like, starting from the elegantly tiny compiler near the end of The Art of Prolog and going further with practical examples -- systems administration tasks with Marelle, maybe show Constraint Handling Rules, et cetera.

One interesting application of Prolog I've read about is using the language to implement build systems a la make and CMake.

Most (all?) of the build systems out there today (make, CMake, rake, etc.) are declarative but they lack Prolog's inference capabilities. This gives a specific advantage -- it allows you to reduce fragility of your build system by making it dead simple to tell when you've combined incompatible configuration options (e.g., compiler flags) which you might otherwise discover halfway through a long build.

For a quick overview, check out the paper prom: A flexible, Prolog-based make tool[1].

[1]: http://www.cs.vu.nl/~kielmann/papers/THD-SP-1991-04.pdf

I'd been thinking about just this recently. But to my mind, you don't even have to implement a build system - prolog can be directly used as one (modulo some library functions). You specify a goal, and a bunch of rules that have build-related side-effects, and then building a "target" is just a query. The syntax is even pretty similar to make, minus all the inexhaustible and unintuitive intricacies.

Two things that you'd get, that to the best of my (limited) knowledge aren't possible in make, is having cut, and the notion of both "and" and "or" - not only can you declare multiple dependencies and rules, but also "alternative" rules in case one does not succeed (e.g., in case you shell-out to a non-existent binary, try a different one).

But then you would manually have to create a list of incompatible flags. There's no way Prolog can know which gcc flags mess with your program.

Correct. It could be broken down into two parts though:

* One database containing facts about which GCC flags are incompatible with one another (i.e., cases where you can't specify both --foo and --bar). This would ideally be provided as part of the build system itself, since it's not going to change for every program built with the system.

* A small database (if one is even needed) you'd specify in your build scripts where you can enumerate specific flags or compiler features you know shouldn't be used with your program. This would augment the database provided by the build system for your specific compiler.

Note, I'm not suggesting that using Prolog to define a build system would make it impossible to specify bad or incompatible compiler flags. I am suggesting that deriving the set of flags to use for a build based on known facts about the compiler being used and your program makes it much less likely that a change you make to a build script causes the build to break in subtle ways once you've started compiling (or worse, at run-time). With Prolog, it'd be easier to detect such issues up-front so you can fix them before you start compiling or deploying.

Every time I've started to learn prolog, I feel like it's too much about the language and nothing about the environment.

I realize that prolog is a language, but it's much harder to learn things when they are purely abstract. A good implementation and a good library go a long way.

I don't have a problem with non-mainstream languages. I like erlang.

I tried learning haskell, too. I didn't get hung up on monads; I ran into a wall when I found out there was no good way to use haskell as an embedded language or call a haskell library from something else without pulling in a big runtime (which interferes with non-trivial host applications). Correct me if I'm wrong.

We use Sicstus Prolog, which we connect to .Net by a provided set of interface-classes

It also has a bi-directional interface to Java, but Sicstus is unfortunately neither free nor cheap

IBM's Watson system is partially written in Prolog:

http://asmarterplanet.com/blog/2011/02/the-watson-research-t...

(see the answers to questions #3 and #6)

Are there any recommended implementations out there of using prolog with RDF? I feel like prolog could offer some interesting trade-offs for working with RDF over SPARQL and I'd be curious to give it a shot.

I feel a disturbance in the Semantic Web - as if a million palms slapped into faces all at once and €100m got spent on nonsense.

To explain - many people spent many eons trying to reason with RDF, OWL and so on, and it hasn't gone too well. The problem is that writing logical statements is very hard, and writing knowledge bases is harder, and writing distributed knowledge bases is hardest of all, and none of this and nothing has sorted out the knowledge engineering bottleneck.

And encoding it in XML does not help.

About 10 or 12 years ago I spent a lot of time experimenting with the semantic web library for SWI-Prolog and it was time well spent. In modern times, commercial/community versions of tools like Star Dog are probably a better place to start experimenting with what OWL reasoning (or RDFS or RDFS+) can do. On great use is being able to mix and match different RDF data sets without translating to a common Ontology.

I have written a few semantic web books and I guess I am still a fanboy, but I also agree with you that "classic" semantic web apps using the W3 standards have had only partial acceptance into mainstream use while similar graph based systems like Knowledge Graph affect how many people use the web (at least for search, Google Now, etc.).

How hasn't it gone too well? Many, many well known companies outside of the technology space including Fortune 100s and 500s as well as various government agencies are successfully leveraging semantic web technologies for knowledge management. There are many interesting public databases out there being widely used for research that leverage semantic technologies as well. JSON serializations of RDF exist too. See: https://dvcs.w3.org/hg/rdf/raw-file/default/rdf-json/index.h...

Public database examples: http://flybase.org/ , http://dbpedia.org/ , http://disease-ontology.org/

Ok, how about

http://www.itjobswatch.co.uk/jobs/uk/semantic%20web.do

Ranking 845 doesn't seem to me to cut it.

I probably use Semantic X more than most people do and I absolutely never understood RDF/OWL/whatever. My use case: I run a fairly large wiki, we have Semantic MediaWiki installed, and literally the only thing we use it for is setting "facts" on pages that you can use as a search engine to find the pages that satisfy queries. It's just metadata for pages, essentially.

I don't think I'm alone in this. None of Semantic Web stuff ever really made sense to me.

I've used RDF and SPARQL for a couple of years so I have some thoughts on it. The problem with using it is that while there are standards for it, there are too many standards and they often aren't followed. If the structure of the data has to be inferred and metadata is missing, then there is no way to figure out the structure. Our product was meant to be able to communicate with internal tools as well as external ones because it used RDF. What we ended up doing was hard coding assumptions about the internal tools because certain pieces of information weren't available in the RDF.

The goal of RDF and the semantic web was to make things easy, but after using it, it makes things much more complicated.

Finally, on the topic of encoding. The old defacto standard of encoding RDF was XML. More recently, Turtle[1] has become more popular, and that really helps the human readability of RDF by an order of magnitude.

[1] http://www.w3.org/TeamSubmission/turtle/

Off-topic but related:

Freebase will be closed on March 31, 2015 (largest open collaborative knowledge base): http://www.freebase.com , http://en.wikipedia.org/wiki/Freebase

Freebase has 2,751,614,700 facts, Wikidata has 13,788,746 facts.

Freebase was acquired by Google and their internal Google Knowledge Graph is based on it. Wikidata may import some data of Freebase, but due its stricter guidelines (notability...) many facts of minor will be lost/never migrated. A Freebase dump won't age well, in a lot of cases up-to-date facts from the real world are required. (ex "Who is the current president of the USA?" "Bill Clinton")

Maybe some community project like Archive.org, Apache Foundation, Wikipedia.org, Mozilla can rescue the Freebase community project before it is too late?

I believe the current intention is to move all the Freebase facts to Wikidata. It's been noted on the Wikidata mailing list that the notability requirements for Wikidata are much less strict than for Wikipedia.

Are there any jobs where Prolog is required? Or maybe something like functionaljobs.com, just declarative?

From my point of view (I worked a few years with the language while in academia), there are no real job offers where Prolog makes a difference.

So maybe erlang people prefer a Prolog background but that's it (w.r.t. a job market perspective)

I found a page from 1994(!) asking the same question: https://dtai.cs.kuleuven.be/projects/ALP/newsletter/archive_...

Given that Prolog isn't super-widely used (compared to say, C++), there are going to be a limited number of developers with Prolog expertise. That means companies who use it in their tech stack are generally going to have to hire developers who fit the other qualifications for the role then put them through some internal Prolog training. The listings for such positions probably won't have Prolog as a "required" skill but a "desired" skill.

One other point -- just because there aren't any/many jobs where Prolog is required doesn't mean there aren't many cases where Prolog could be useful. Prolog hasn't been widely taught for a couple of decades, so a significant proportion of developers today won't recognize a problem that Prolog would be a good solution for as a problem that Prolog would be a good solution for.

There's a Strange Loop 2014 talk on YouTube, "Production Prolog", that might give ideas about jobs that use (or could use) Prolog: https://www.youtube.com/watch?v=G_eYTctGZw8

Prolog is really interesting. There's also https://github.com/mcsoto/cosmos which transpiles to Prolog, I believe. It looks like the latter isn't actively worked on, unfortunately.

Windows NT used an embedded Prolog interpreter to configure its networking

https://news.ycombinator.com/item?id=513962

OMG! This is like Christmas morning. Though I learnt BASIC programming language first, Prolog was the first language that blew me off. Part of the reason may be that I learnt Prolog late during my post graduation. It was such a wonderful language with its constructs that gave me a sudden feeling like having wings.

Good. It is such a powerful language. I ended up writing a console game as a side project and was simply thrilled with ability of the program that can "take" decisions and play the game along.

Prolog is really great for some applications. I used it in robotics and RoboCup@Home. The robot built a world model of its surroundings and labeled entities with classes. When a cleanup tasks was given, the robot picked something up, and based on the class, it reasoned where the entity should be moved (e.g table, kitchen or trashbin).

This was in a mechanical engineering group, so it took some time for some people to get used to such e different language.

A year ago I asked about real-world use cases for Prolog, there were a couple of interesting ones: https://www.linkedin.com/groups/Examples-current-realworld-u...

People might not be aware that the JVM (Java Virtual Machine) specification includes a class verifier written in Prolog, see http://docs.oracle.com/javase/specs/jvms/se7/jvms7.pdf

Clementine -- a data mining application purchased by SPSS

SPARK toolset -- a rigorously defined Ada subset used for developing software correct by construction. This approach is used in areas like aviation, transportation, medicine, energy, etc. where failure is not an option.

ECLIPSE-CLP -- an open source constraint logic programming library used to solve various resource allocation problems. Think of it as a poor man's Operation Research expert.

Experian, the credit rating company, bought out Colmerauer's Prologia company: http://www.experianplc.com/news/company-news/2005/25-10-2005...

ContractExpress/DealBuilder from Business Integrity Ltd http://www.business-integrity.com/

InFlow from OrgNet http://www.orgnet.com/

GridMind tool - a for modelling and simulation new technologies implementation into energy grids (smart grids, smart metering etc.). They have to generate detailed complex models satisfying lot of rules which to make models realistic. Prolog together with CLP is excellent tool for that. Fast development, small code, elegant solutions. www.mycroftmind.com

David Warren (Leading Professor at Stony Brook University): "We at XSB, Inc. use Prolog and Java. We use Prolog for knowledge extraction and standardization and for ontology representation. We have (to me, somewhat surprisingly) found that our Prolog code is more stable and we spend less on maintaining it than we do our Java code. It may be programmer skills, but I think it is also due to the much more succinct expression of similar functionality."

The Nokia N900 phone used prolog to do ui state management .... prolog in a smartphone!

London-based startup Texrazor performs text analysis via API and the engine behind it is coded in Prolog http://www.textrazor.com/technology

Prolog does social and organizational network analysis for clients around the world. http://orgnet.com/inflow3.html

Orgnet, LLC also uses LPA Prolog to do data analysis, especially for hidden relationships and patterns in business data... for examples, see: http://thenetworkthinkers.com

etc., see the discussion on LinkedIn

The first Erlang Compiler and VM were implemented in Prolog iirc.

Erlang's syntax was also influenced by prolog.

EDIT: apparently i recalled correctly: http://www.erlang.org/faq/academic.html

Am excited that prolog can be queried by JavaScript. Am doing a project on an interactive chatbot-like pages in javascript. My LOCs was getting extremely large. Any links on sample codes for querying prolog from JavaScript?

Could Prolog be used in geometric constraint solving? Any examples?

It seems to me that Prolog (and Datalog) might have some strengths in querying social graphs for social network applications. Has anyone seen it being used in that way?

The examples could benefit from some syntax highlighting

yes

no.

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