core.logic VS paip-lisp

It's also available in Clojure: https://github.com/clojure/core.logic

If you want to write one yourself, it's pretty easy: https://www.youtube.com/watch?v=y1bVJOAfhKY

Something like Clojure's core.logic would be pretty nice too. As I understand it, this is one of those features that has been re-invented time and again in the Lisp world over the years. Although the CL standard is already fairly large, it would probably be a bit controversial to make that a required part of a CL implementation. Still, it would be cool to have the option of using dependent types in the macro system to generate formerly verified Lisp code at compile time.

It also has core.logic which is minikanren. There are other logic programming options as well. Some libraries like core.typed use core.logic for the type checker.

You could study core.logic: https://github.com/clojure/core.logic/tree/master/src/main/c...

I swear I'd bookmarked a resource that was more analogous to #2, but you may want to have a look at The Little Prover: https://mitpress.mit.edu/books/little-prover

related:

https://github.com/clojure/core.logic/wiki/A-Core.logic-Prim...

PAIP by Peter Norvig, Chapter 23, Compiling Lisp

https://github.com/norvig/paip-lisp/blob/main/docs/chapter23...

Emacs is so much more than a text editor! But I need to stay on topic...

I believe your assessment of LISP (and therefore of MacArthy)'s impact on AI to be unfair. Just a few days ago https://github.com/norvig/paip-lisp was discussed on this site, for example.

Sounds like a great project idea to make a toy demo of this direction you'd like to see. Maybe comparable to https://github.com/norvig/paip-lisp/blob/main/docs/chapter15... and https://github.com/norvig/paip-lisp/blob/main/docs/chapter8.... which are a few hundred lines of Lisp each, but do enough to be interesting.

You could look into Paradigms of AI Programming by Peter Norvig which might interest you regardless of Lisp content.

Lisp has great power, examine PAIP, part II chapters 7 and 8.

A computer running Prolog reasons, and that only requires a couple of pages of code. So it seems feasible that the network could have learned some ability to reason within its network.

IMHO it's because lisp shines to manipulate symbols whereas the current AI trend is crunching matrices.

When AI was about building grammars, trees, developing expert systems builds rules etc. symbol manipulation was king. Look at PAIP for some examples: https://github.com/norvig/paip-lisp

This paradigm has changed.

Origen: Conversación con Bing, 4/4/2023(1) gigamonkey/monkeylib-binary-data - GitHub. https://github.com/gigamonkey/monkeylib-binary-data Con acceso 4/4/2023. (2) paip-lisp/chapter4.md at main · norvig/paip-lisp · GitHub. https://github.com/norvig/paip-lisp/blob/main/docs/chapter4.md Con acceso 4/4/2023. (3) bibliography.md · GitHub. https://gist.github.com/gigamonkey/6151820 Con acceso 4/4/2023.

If anyone is interested PAIP is downloadable at https://github.com/norvig/paip-lisp