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Super cool. I dig generating rules from within the LLM, but I'm not sure Prolog is the right choice in 2024.

I love Prolog and had the opportunity to use it "in anger" years ago to handle temporal logic in a scheduling app. Great experience, but I've found that more modern rules engines like Drools (anything using the Rete algorithm) are a MUCH better fit for most use cases these days.

If you are into this stuff, you might like the talk I gave on rules engines, prolog and how it led to erlang & elixir. https://www.youtube.com/watch?v=mDnntrhk-8g&t=1s



The choice is limited to the languages that LLMs already know really well. Fwiw, here is GPT's self-rating out of 10:

Python: 9, Prolog: 7, Datalog: 6, Mercury: 6, Curry: 5, Drools: 4

This is not even the full set of what the LLM might like to use. It may also like pyDatalog, SymPy, Haskell, Clingo ASP, ECLiPSe CLP, etc.


Drools is a rules engine, but Prolog is a fully-fledged, general-purpose language, yes? For example SWI-Prolog has a bunch of http libraries and can be used as a web development language (using Prolog's clause database itself in place of some SQL). I don't think that'd be a sensible use case for Drools.


You can use drools from Java as a library probably.




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