hebigo VS paip-lisp

The Lissp transpiler incrementally compiles and executes each top-level form to Python. It needs to do this in case there's a macro definition that might affect the compilation of a subsequent form. If it's only executing definitions, this is harmless, but if you want to precompile the main module, it needs the guard, or the side effects will happen too.

If you want Python to be as customizable as Lissp, check out Hissp (and Hebigo).

Python's lambdas can have as many lines as you want. Just wrap parens around it. Hissp uses this form as a compilation target. Its REPL shows the Python compilation. Play around with it til you get it: https://github.com/gilch/hissp

The original Lisp's S-expression syntax was just supposed to be an intermediate language used by the compiler when processing the real language based on M-expressions, which kind of never took off. Numerous alternatives to S-expressions have been proposed, and some retain homoiconicity, another feature diagnostic of a Lisp (and one that ECMAScript lacks). For example, see Hebigo's readme, which shows a direct correspondence between its Python-like syntax and that of Hissp's default reader (Lissp), which uses the S-expressions. Julia can also be written in S-expressions, but this usually only used in macro definitions.

I think LoL is too CL-specific. If you know both languages first, you can pretty much translate, but since they'd be trying to learn Lisp in the first place, this is a bad idea.

On the other hand, [Hissp][1] has a pretty good tutorial for anyone coming from a Python background.

[1]: https://github.com/gilch/hissp

Hebigo: a whitespaceLisp isomorphic to Hissp that looks like Python.

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