this is very cool, ivan!  two suggestions would be to indicate on the ovals 
with a tick mark where the off-screen nodes are to guide navigation, and a 
permanent slider/[+,-] buttons for global zoom control.  (i know these are 
obvious)

On Tuesday, July 13, 2021 at 7:15:09 AM UTC-4 [email protected] wrote:

> 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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