While waiting for inference histories, I'm developing an idea about turning
the inference visualizer into an interactive AtomSpace debugger:
http://ocog.atspace.cc/.

pon, 12. srp 2021. u 21:43 Ivan V. <[email protected]> napisao je:

> Great, I'm glad you are interested in an experiment.
>
> A reasonable step would be for Nil to send you some real PLN and URE
>> inference histories and see what your visualizer does with them...
>>
>
> Sure, JSON history files would be perfect (we could make this a standard
> communication pipe between reasoner and visualizer), but I guess I can
> somehow manage any existing format you are already used to. You know my
> mail.
>
> Currently, the library is AJAX-ing an XML tree structure and standard
> HTMLs as input, with possibility of using php or other server side
> scripting technology to interface the input files you pass over here. Would
> that be ok? I have to mention, with some additional effort, there could be
> other input options such as reading and evaluating JSON file wrapped into
> javascript source code file. I'm telling this because this would exclude
> the requirement of running a HTTP and php server, but if it is not
> necessary, I'd like to avoid this step and do the php trick.
>
> pon, 12. srp 2021. u 20:30 Ben Goertzel <[email protected]> napisao je:
>
>> A reasonable step would be for Nil to send you some real PLN and URE
>> inference histories and see what your visualizer does with them...
>>
>> On Mon, Jul 12, 2021, 10:59 AM Ivan V. <[email protected]> wrote:
>>
>>> I made a small infinity test <http://ocog.atspace.cc/infinite/> too.
>>> Each parent virtually has an infinite number of children. Rolling ovals
>>> around, zooming ovals in, zooming ovals out, ... Surely it's not exactly
>>> perfect, but I could live with it.
>>>
>>> pon, 12. srp 2021. u 17:48 Linas Vepstas <[email protected]>
>>> napisao je:
>>>
>>>> Hi Ivan,
>>>>
>>>> On Mon, Jul 12, 2021 at 6:00 AM Ivan V. <[email protected]> wrote:
>>>>
>>>>>
>>>>> Thank you for asking, and my thoughts are pretty obvious. As I
>>>>> understand, URE and PLN are all about proofs, so my thoughts may go in 
>>>>> that
>>>>> direction. Suppose we have a natural deduction proof composition:
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> *  ---   ---   ---     ---   ---   ---     ---   ---   ---   I     J
>>>>>   K       L     M     N       P     Q     R -----------------
>>>>> -----------------   -----------------         A                   B
>>>>>           C-----------------------------------------------------------
>>>>>                        X*
>>>>>
>>>>> You can already see the tree-like composition, but as it may span over
>>>>> a very wide and tall area, it may be required to represent it within an
>>>>> on-demand scaling system. This example <http://ocog.atspace.cc/>
>>>>> roughly shows what I have imagined for proof representation. In the 
>>>>> example
>>>>> you can play with ovals, dragging them around and in or out the central
>>>>> area, zooming proof parts of the current interest. Notice how it is
>>>>> possible to represent and navigate nearly infinite length proofs, assuming
>>>>> enough memory space.
>>>>>
>>>>
>>>> Re: navigating trees: if you don't already know this, then I suggest
>>>> that you really, really should study hyperbolic rotations aka mobius
>>>> transformations on the poincare disk. They implement your example.  I
>>>> recall seeing a demo of this at SIGGRAPH two or three decades ago. As you
>>>> pan around on the hyperbolic disk, different parts of the graph get
>>>> magnified at the center. And, like an MC Escher print, the rest of the
>>>> graph remains compressed at the edges.
>>>>
>>>> For scale-free networks, this doesn't work. And from what I can tell,
>>>> learning really does result in something close to scale-free networks.
>>>> What this means in practice is that there's one vertex with a million edges
>>>> coming off of it.  There are two, with half-a-million each. Four, with a
>>>> quarter-million each, and so on. So almost all vertexes have just a handful
>>>> of edges connected to them, but as you move around, from vertex to vertex,
>>>> you bump into these monsters. And you can't really draw them: try drawing a
>>>> vertex with a thousand edges on your 2Kx2K monitor: most of those edges
>>>> will be less than one pixel from each-other. It'll be just a big blob.
>>>>
>>>> It's important to "eat your own dog-food", as they say, or "smoke your
>>>> own dope": use your own code to solve actual, real-world problems. This
>>>> very quickly highlights where all that beautiful theory doesn't quite work
>>>> out in practice.
>>>>
>>>> --linas
>>>>
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