Yes! I love it when people give definite answers.
So, just to check, the preferred language is Scheme?
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The prefered language is atomese. http://wiki.opencog.org/w/Atomese
scheme is there for accidental historical reasons, it just happens to be a really good fit for typed hypergraphs. Java is a terrible fit, it doesn't have this concept. Javascript feels like it might fit well. Python is awkward -- again, cause both python and java are procedural languages, not functional, and thus have no concept of hierarchy or recursion or any graph-like structure.The atomspace is defacto implemented in c++ partly for historical reasons, and partly because that provides OK performance.--linas
On Wed, Jul 26, 2017 at 3:06 PM, Ed Pell <edp...@gmail.com> wrote:
Yes! I love it when people give definite answers.
So, just to check, the preferred language is Scheme?
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I mean -- just making another scripting-language wrapper for Atomspace
and associated cognitive-process interactions doesn't really
accomplish anything, that's all...
Right now we have bindings in Scheme, pretty-thorough ones in python,
very partial ones in Haskell ... but pretty much only the Scheme ones
are used by anyone. I have been debating whether we should just
deprecate the python and Haskell bindings...
Here are example implementations for other scheme dialects
https://github.com/Calysto/calysto_scheme
https://github.com/joeltg/mit-scheme-kernel
Please don’t deprecate the Python bindings. We’re out here. We don’t speak up because we’re still light years behind where you folks, the stars of the OpenCog Universe, are and we have nothing of value to contribute…. Yet. But we’re here, and we have developed a great deal of the structure into which we want to eventually nest OpenCog as the central cognitive organizing structure. And we’ve developed most all of that in Python J
Dave
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I can see your points, sometimes I forget how ambitious this project is... :)I suppose you want to make the software do what you want by communicating with it in a natural language and extend its capabilities on its own if it cannot achieve something yet by learning.
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