On Mon, Dec 31, 2012 at 5:30 PM, Aaron Hosford <[email protected]> wrote:

> Logan,
>
> Why not use C?
>

doesn't support recursion, or return arguments.
my programming style requires both those.


> It's highly portable, and it's easier to read, understand, write, and
> modify. Assembly isn't comparably faster enough to justify the
> significantly greater time it takes to write it, and you can always
> optimize important loops to assembly later.
>

It's easier for me to read understand, write and modify, only 16 functions
hey it's a breeze :-).



>
> I'm using Python for the prototyping language for my own projects.
>

8-| boggle eyes, I don't know how you manage.


> Python is specifically tailored for clarity and rapid development, so I
> can focus on my ideas instead of how to effectively use the language.
>

Really? when I was using python, I was only met with frustration, and
constant searching through annals of libraries, much as with Java.
Haskell kinda broke down once project got too big,
or rather required things easier with mutable variables.


> I can easily port key parts of it to C or even assembly later on should
> efficiency become a problem. The time savings I gain from being able to
> rapidly test ideas and try out new approaches is invaluable. I can write or
> rewrite an entire system from scratch in mere days instead of months or
> even years, so my only slowdowns come from actually thinking about the
> design, rather than coding.
>

I can say all the same things for assembly.
Coding is really the smallest part of what I do.
my changelog is almost twice the size of my sourcecode,
it's where I discuss various project ideas in print.

I think a lot of it has to do with how you use it.
Like C and c++ with all their types and checks,
it's just a big headache like I dono can't deal with limits,
I like freedom, being able to do what I want, how I want.

Like I'm willing to dig through the libraries of some high level language,
if I want to make a bugfix to some open source project I'd like to make
function on my computer.
Or if some task specific language is available, like PHP for making
websites.

Though for the task at hand, i.e. making HSPL, assembly is the best.
Since I use register-machine assembly, mostly I just write the algorithm,
load variables, and call functions then return, it's very simple, and
little coding.  no try catch loops or odd throws.

GDB is completely satisfying for debugging purposes.



>
> On Fri, Dec 28, 2012 at 5:09 PM, Logan Streondj <[email protected]>wrote:
>
>> Hey I'm just offering you support to do some real coding.
>> It's good to get the ideas into something more tangible like programs.
>>
>> If you find that after whichever period of time you aren't getting much
>> anywhere with your chosen route, perhaps you'll choose to contribute to
>> another AGI project, perhaps my own.
>>
>> I did a version release today, now have support for primitive variables
>> :-).  By next version release quite possibly will be able to do  factorial
>> or some other simple procedures.
>> And likely by next year will have English grammar,
>> allowing for easier verification by others with smaller learning curve.
>>
>> I'm programming in Assembly, but it is quite simple,
>> only 16 assembly commands used, all register-machine,
>> makes it easy to port and that kinda stuff.
>>
>> You would certainly have the capacity to improve upon current AGI
>> programs,  can look at the current roadmap and see where your ideas might
>> fit in
>> https://sourceforge.net/p/rpoku/code/ci/dc0d7886965d5cab645a4d5a220391b316c7c388/tree/roadmap.txt?format=raw
>>
>>
>> On Fri, Dec 28, 2012 at 10:53 AM, Jim Bromer <[email protected]> wrote:
>>
>>> The most important case would be the one where it does show some
>>> capability of learning a crude simplistic language but where it either
>>> lacks subtlety or where it shows a wide variation of depth.  In some cases,
>>> for example, it might seem to be working but then it just cannot continue
>>> to learn new things about a particular subject or where other subjects
>>> which are comparably as easy seem to be totally beyond it. This is along
>>> the lines of how other AI projects have fared.  Let's say that my project
>>> did turn out like this.  Then in order to show that it was a valid concept
>>> I would have to advance the program so that it was able to go further than
>>> it had.  The thing is that although the various AI methods are able to do
>>> some tasks better than others they all fail at a level below what we need
>>> to see in order to compare them to children.  So being human like is not
>>> the immediate goal, and being really smart is not the immediate goal. But I
>>> would need to show that I could improve on contemporary AGI programs in
>>> order to demonstrate that my ideas were workable and since my program would
>>> be limited I would need to show that some improvements could be made to my
>>> program.
>>>
>>> Jim Bromer
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