ciao VS Gleemin

Some Prolog systems (like Ciao Prolog https://github.com/ciao-lang/ciao/blob/master/core/lib/forei...) implement bidirectional foreign interfaces. Once you have C bindings it is easy to write bindings from Rust, C++, or any other language (that can interoperate with C). I give here some details about Ciao because this is the system I know better but it should be similar for other popular Prolog implementations.

The tradeoffs depend on the complexity of the Prolog code and your needs for performance and features: pure LP, Prolog (search+unification+cut), garbage collection, dynamic database updates, constraint domains, etc. The Ciao Prolog engine is around 300-400KB. Adding a few libraries, compiler, etc. it goes to 2MB. Naive Prolog systems can be one order of magnitude smaller at the cost of sacrificing ISO compatibility, performance, etc. Note that "performance" can be very misleading. Some Prolog programs may run particularly fast in some Prolog system and very badly in others.

Here's some stuff I've written in Prolog, some for my own enjoyment, one for my degree project.

Most of the benefits I found come down to two things:

a) Prolog, like the various kanrens, is a relational language so a program is effectively a database. There's no need to do anything special to glue together a data layer and a logic layer, because you have both written in Prolog.

b) Prolog's declarative style makes translating rules and directives to code a breeze. The three projects below are all games and benefit heavily from this feature. I

1. Warhammer 40K simulation:

https://github.com/stassa/wh40ksim

Runs simulations of combat between WH40k units.

2. Gleemin, a Magic: the Gathering expert system:

https://github.com/stassa/Gleemin

Doesn't work anymore! Because backwards compatibility. Includes a) a parser for the rules text on M:tG cards written in Prolog's Definite Clause Grammars notation, b) a rules engine and c) a (primitive) AI player. The parser translates rules text from cards into rules engine calls. The cards themselves are Prolog predicates. Your data and your program are one and now you can also do stuff with them.

3. Nests & Insects, a roguelike TTRPG:

https://github.com/stassa/nests-and-insects

WIP! Here I use Prolog to keep the data about my tabletop rpg organised, and also to automatically fill-in the character sheets typeset in the rulebook. The Prolog code runs a character creation process and generates completed character sheets. I plan to do the same for enemies' stat blocks, various procedural generation tables, etc. I also use Prolog to typeset the ASCII-styled rulebook, but that's probably not a good application of Prolog.

You asked about "logic programming" in general and not miniKanren in particular. I haven't actually used miniKanren, so I commented about the logic programming language I've used the most, Prolog. I hope that's not a thread hijack!

All three of the projects above are basically games. I have more "serious" stuff on my github but I feel a certain shortfall of gravitas, I suppose.

official name):

https://github.com/stassa/Gleemin/blob/master/mgl_interprete...

The first two-thirds of the source in the linked file is a grammar of a subset

I've been keeping an eye on this to use for the rules engine in a card game I'm writing[0]. Very excited to get back into using Prolog; I think it's fallen by the wayside a bit in the last decade or two but there's some sectors that still have strong arguments for using it if not as the main language then at least an extension language.

[0] Inspired by a HN comment a while back about Gleemin, the MTG expert engine in Prolog: https://github.com/stassa/Gleemin

Representing costs in a meaningful manner is a constant problem in every M:tG generator I've seen.

The problems I highlight above are not with grammaticality, which is certainly a big step forward with respect to the past. But many of the abilities still don't make a lot of sense, or don't make sense to be on the same card, or have weird costs etc.

My intuition is that it would take a lot more than language modelling to generate M:tG cards that make enough sense that it's more fun to generate them than create them yourself. I think it would be necessary to have background knowledge of the game, at least its rules, if not some concept of a metagame.

Also, I note that the new online version of the game is capable of parsing cads as scripts in a programming language using a hand-crafted grammar rather than a machine-learned model [4] [5]. So it seems to me that the state-of-the-art for M:tG language modelling is still a hand-crafted grammar.

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[1] https://github.com/stassa/Gleemin - unfortunately, doesn't run anymore after multiple changes to Prolog interepreters used to create and then port the project over.

[2] https://github.com/stassa/THELEMA - should work with older versions of Swi-Prolog, unfortunately not documented in the README.

[3] https://link.springer.com/article/10.1007/s10994-020-05945-w - see Section 3.3 "Experiment 3: M:tG fragment".

[4] https://www.reddit.com/r/magicTCG/comments/74hw1z/magic_aren...

[5] https://www.reddit.com/r/magicTCG/comments/9kxid9/mtgadisper...