Matt, Ben, FYI, I've been developing a suite of tools/API's that might be useful for this. Getting tonini phi is "easy" .. or hard depending on what exactly you want. So...
at the core, there's an API to expose a portion of the atomspace as a matrix. You can think of it as a correlation matrix, covariance matrix, adjacency matrix of a graph, etc. The "adjacency matrix of a graph" is the viewpoint you want for IIT. A set of stuff you can do with the matrix, including computing it's entropy, MI,various RMS deviations. Doing PCA to it. Also, cutting it in various aways: Currently, I'm using the cuts to filter out noise and junk data, but you could use the cuts to perform the tonini cuts. The "hard part" is that computing entropy for a 30K x 30K matrix can take hours... so that limits just how many cuts you can explore. To use this toolset, you need to write a shim that specifies how to get the matrix element (i,j) and some related info: the atom type of all the i's the atom type of all the j's, the atom type of the pair (i,j), and where to store per-row and per-column data (for subtotals of various kinds) I'm actively hacking this now, so its a bit unstable and maybe buggy. Code is here. https://github.com/opencog/atomspace/tree/master/opencog/matrix --linas On Fri, Jun 16, 2017 at 7:02 AM, Matthew Ikle <[email protected]> wrote: > Of course — that is why I called it a pre-experiment. There are some > subtle mechanics (distribution determination, system partitioning) that we > need to work out in the actual calculations for phi (or phi*) and the > approach I outline will allow us to concentrate on figuring these out. Once > we know how to perform these calculations for this simple pre-experiment, > then we can more easily add complexity to it by extending and modifying it > to the AF and/or WA. And of course connecting IIT with strange attractor > formation would be the “holy grail” of the entire pipeline of experiments, > > —matt > > > On Jun 15, 2017, at 9:19 PM, Ben Goertzel <[email protected]> wrote: > > > > 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 > > -- > You received this message because you are subscribed to the Google Groups > "opencog" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > To post to this group, send email to [email protected]. > Visit this group at https://groups.google.com/group/opencog. > To view this discussion on the web visit https://groups.google.com/d/ > msgid/opencog/57F4DB20-446A-4565-AA3D-D7C4FFFD3762%40gmail.com. > For more options, visit https://groups.google.com/d/optout. > -- You received this message because you are subscribed to the Google Groups "opencog" group. 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