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Gleemin Alternatives
Similar projects and alternatives to Gleemin
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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expr
Discontinued Expression language and expression evaluation for Go [Moved to: https://github.com/expr-lang/expr] (by antonmedv)
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chalk
An implementation and definition of the Rust trait system using a PROLOG-like logic solver (by rust-lang)
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SaaSHub
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ciao
Ciao is a modern Prolog implementation that builds up from a logic-based simple kernel designed to be portable, extensible, and modular.
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microKanren-py
Discontinued Simple python3 implementation of microKanren with lots of type annotations for clarity
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mediKanren
Proof-of-concept for reasoning over the SemMedDB knowledge base, using miniKanren + heuristics + indexing.
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Gleemin reviews and mentions
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Annotated implementation of microKanren: an embeddable logic language
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.
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50 Years of Prolog and Beyond
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
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An embeddable Prolog scripting language for Go
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
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The Computers Are Getting Better at Writing
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...
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The primary programming language of Gleemin is Prolog.
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