Yes, that would be a meaningful experiment to start with, though
obviously not a substitute for an experiment that gauges the
integrated information of the dynamics more broadly...

On Fri, Jun 16, 2017 at 12:54 AM, Matt Ikle <[email protected]> wrote:
> Hi Ben,
>
> I've been thinking a lot about how to actually create experiments for
> connecting ECAN with Phi.
>
> It seems to me that a simple pre-experiment we could run builds upon the
> insecticide experiment as follows. We could load the insecticide experiment
> background knowledge and then stimulate the atoms for poison and insects
> just as before. We can track STI values for these three atoms over time and
> calculate IIT time series values from the STI time series values. To do this
> means making only some minor modifications to the practical_phi toolbox
> Matlab code to find IIT.
>
> We may even be able to, though I am more unsure about this, build upon this
> simple experiment to detect attractor formations within ECAN dynamics prior
> to looking at the larger ECAN dynamics using PLSI to reduce the space.
>
> Just trying to create a simple first set of experiments. Thoughts?
>
> --matt
>
> Sent from my iPhone
>
> On May 23, 2017, at 10:18 AM, Ben Goertzel <[email protected]> wrote:
>
> Yes, agreed...
>
> On May 24, 2017 00:15, "Matthew Ikle" <[email protected]> wrote:
>>
>> Yes all of this makes a lot of sense and could be exciting, especially the
>> connection to Phi. Could be an extremely interesting paper — but a lot will
>> depend upon parameter tuning as well as creating an appropriate experiment.
>>
>> Before we begin setting up the experiment to look for connections between
>> Phi and strange attractor structure, though, we obviously must first ensure
>> basic ECAN implementation as follows:
>>
>> Step 1: Ensure that ECAN works correctly and fulfills basic design
>> criteria;
>> Step 2: Run poison experiment and retune parameters.
>>
>> I feel confident that after Misgana makes the minor changes we discussed
>> in HK, ECAN should work correctly. Only after we have run through the two
>> steps above, though. should we proceed with the next (IIT) step and perform
>> additional parameter tuning.
>>
>> At some point (probably after all of the above), we should also enable
>> HebbianLink updating and run experiments testing the three updating
>> equations we have developed and setting the stage for yet another set of
>> parameter tuning.
>>
>> —matt
>>
>> > On May 23, 2017, at 3:52 AM, Ben Goertzel <[email protected]> wrote:
>> >
>> > Matt,
>> >
>> > Thinking about how to analyze time-series data from ECAN, I thought it
>> > might be cool to look for interactions between IIT (Phi) and strange
>> > attractor structure in the attentional focus...
>> >
>> > I found this code which lets us analyze data using Integrated
>> > Information Theory (Tononi's Phi)
>> >
>> > https://figshare.com/articles/phi_toolbox_zip/3203326
>> >
>> > This has gotten some acceptance as a "measure of consciousness", so if
>> > we could show that some ECAN parameters or aspects correlate with
>> > "degree of consciousness" as measured by Phi, this would let us
>> > publish a wizzy and popular paper....   For instance, what if the
>> > system was more conscious (higher Phi) when it connected a sentence
>> > with background knowledge, than when it parsed a sentence but was
>> > unable to connect it with background knowledge...
>> >
>> >
>> > On the other hand, another interesting thing to do would be to look at
>> > a delay-embedding of the dynamics...
>> >
>> > Long ago I used the TISEAN toolkit for nonlinear time series analysis
>> >
>> > What I am thinking here is: If we are loading in Atoms from a bunch of
>> > texts, we could run PLSI or similar (latent semantic indexing) on the
>> > texts (Eyob could help with that, he's a master of PLSI), to create a
>> > dimensional space.   At any moment in time, the WordNodes and named
>> > ConceptNodes in the AttentionalFocus would then assign the AF a
>> > certain point in the dimensional space defined by the PLSI factors.
>> >
>> > This would turn the AF into a trajectory in n-dimensional space...
>> >
>> > One could then use some approach to figure out the optimal delay and
>> > do a delay-embedding of this trajectory, hopefully revealing the
>> > underlying attractor structure...
>> >
>> > TISEAN seems only to do delay embedding from 1D time series
>> >
>> > https://www.pks.mpg.de/~tisean/Tisean_3.0.1/index.html
>> >
>> > but there are papers explaining how to do it from multi-D time series
>> >
>> > https://arxiv.org/pdf/nlin/0609029.pdf
>> >
>> > https://arxiv.org/pdf/1409.5974.pdf
>> >
>> > Showing that the AF contents occupy a certain strange attractor --
>> > maybe shifting which strange attractor over time, or shifting the
>> > shape of the strange attractor over time, would be interesting
>> >
>> > Some association between the Phi (IIT) value and some property of the
>> > inferred attractor would also be interesting...
>> >
>> > -- Ben
>> >
>> >
>> >
>> >
>> > --
>> > Ben Goertzel, PhD
>> > http://goertzel.org
>> >
>> > "I am God! I am nothing, I'm play, I am freedom, I am life. I am the
>> > boundary, I am the peak." -- Alexander Scriabin
>>
>



-- 
Ben Goertzel, PhD
http://goertzel.org

"I am God! I am nothing, I'm play, I am freedom, I am life. I am the
boundary, I am the peak." -- Alexander Scriabin

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