Re: [FRIAM] FRIAM and causality
-BEGIN PGP SIGNED MESSAGE- Hash: SHA1 Phil Henshaw on 12/07/2007 01:42 PM: > PH: I was impressed with the clarity of the abstract and their not > confusing biology, lab chemistry and computer model references. Figure > 1 puzzles me though. I get your suggestion that this shows a way people > are using new visualization techniques to compare models. I don't > understand how highly complex comparisons of test tube and computer > based things would make them look so very much alike unless both are > parametric data displays of a sort not described, though. Comparing > hugely complicated systems does need visualization help, certainly, but > if that's what makes the images look so much alike it should be > mentioned. Still, what I get from the picture is that they give > themselves an A+. I don't see how their model recreates some features > of the natural process and interestingly leaves others out. It's > importantly that art of making what you've failed to account for > interesting, rather than hiding it, that I find missing in lots of > studies. Just for clarity, it's a cartoon and not a visualization. The diagram is merely intended to give a visual impression of the iterative process being used. The gray smudges and spots representing targeted attributes do not map to particular behaviors of the in vitro or in silico models. So, it's not that they're giving themselves an A+, they're just trying to say that the first model (the gray circle in A) is falsified because it doesn't exhibit the behavior indicated by the spot labeled "a" even though it exhibits the behaviors labeled "t". The second model (not just the same model with different parameter values), pointed to by "2" in B is _also_ falsified because it does not exhibit "a". However, there are indications that model 2 is "better" than model 1 because it exhibits those two behaviors indicated by the spots that are closer in the behavior space to "a". The subsequent model 3 is _validated_ because it exhibits behaviors "t" and "a". > So, here's to all 'bad' models...! may we survive them...:-) Perfect! I'll make that toast over my next pint. - -- glen e. p. ropella, 971-219-3846, http://tempusdictum.com The only good is knowledge and the only evil is ignorance. -- Socrates -BEGIN PGP SIGNATURE- Version: GnuPG v1.4.6 (GNU/Linux) Comment: Using GnuPG with Mozilla - http://enigmail.mozdev.org iD8DBQFHWcv/ZeB+vOTnLkoRAsDcAJ97VJWKqW1O7XZjfvRqJccektNC3QCgn1fV TJh+giOWVLF9kvPtmpfVoi0= =sxCj -END PGP SIGNATURE- FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
Re: [FRIAM] FRIAM and causality
Glen, > > Phil Henshaw on 12/06/2007 10:53 AM: > > The hard part seems to be to take the first dark step to accepting > > there might be a shape of another form that the measures > are missing > > (like the whole tree or person). It means looking for how to best > > extend and complete your image based on the limited cast of the > > measures at hand. Interpolation gone wild?? Free form projection > > perhaps?? Sort of... You just gotta do something to make > sense of the > > larger continuities that develop in natural complex > systems. What I > > think we can see clearly is that our measures and models are highly > > incomplete. > > I think we agree, which normally means there's nothing to > talk about! [grin] But, I thought I'd throw out my term for > what you're describing: "triangulation". > > It's not really triangulation, of course. But it's certainly > more like triangulation than, say, population sampling. > Perhaps we could call it "tuple-angulation"??? [grin] PH: I guess I just call it filling in the gaps, understanding that as a combination of analysis and synthesis. So, if 'gaps' then become a raw material for systems science part of what makes a model 'good' is if you can see how it is also interestingly 'bad', since without having some interest in the 'bad' you can't be tracking the usually moving and significantly misrepresented targets of the physical system.. :-,) I do come close to 'triangulation' in my derivative reconstruction method, except I use 4 points to find a 5th rather than 2 points to find a 3rd. Given 5 points in time sequence it imputes a new value for the middle one, based on the making the implied 3rd derivatives from right and left the same (going forward and back in separate passes and averaging). If each point is considered a separate "bad" model for the system one could impute an average value and a system having a single fixed average state. Using derivative reconstruction imputes a continuous complex process without fixed definition instead. That seems to be a less distorting way of data smoothing, and more useful for raising questions about the turning points within the changing mechanisms producing it. > Here's a paper in which "we" (i.e. my outrageous rhetoric is > reigned in and made coherent by the authors of the paper ;-) > try to describe it: > http://www.biomedcentral.com/1752-0509/1/14/abstract >See Figure 1. This particular example is just one sub-type of the general method we're talking >about, here, though. PH: I was impressed with the clarity of the abstract and their not confusing biology, lab chemistry and computer model references. Figure 1 puzzles me though. I get your suggestion that this shows a way people are using new visualization techniques to compare models. I don't understand how highly complex comparisons of test tube and computer based things would make them look so very much alike unless both are parametric data displays of a sort not described, though. Comparing hugely complicated systems does need visualization help, certainly, but if that's what makes the images look so much alike it should be mentioned. Still, what I get from the picture is that they give themselves an A+. I don't see how their model recreates some features of the natural process and interestingly leaves others out. It's importantly that art of making what you've failed to account for interesting, rather than hiding it, that I find missing in lots of studies. So, here's to all 'bad' models...! may we survive them...:-) Best, Phil - -- glen e. p. ropella, 971-219-3846, http://tempusdictum.com If this were a dictatorship, it would be a heck of a lot easier, just so long as I'm the dictator. -- George W. Bush -BEGIN PGP SIGNATURE- Version: GnuPG v1.4.6 (GNU/Linux) Comment: Using GnuPG with Mozilla - http://enigmail.mozdev.org iD8DBQFHWX6LZeB+vOTnLkoRAhfiAJ4ldUf3p2wtlih3736TIp28uVtEZACfWyMf Pi/MX4iy1xD4PrqQNyNvbYo= =9GWs -END PGP SIGNATURE- FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
Re: [FRIAM] FRIAM and causality
Phil Henshaw wrote: > The hard part seems to be to take the first dark step to accepting there > might be a shape of another form that the measures are missing (like the > whole tree or person). Glen E. P. Ropella wrote: > See Figure 1. This particular example is just one sub-type of the > general method we're talking about, here, though. > Figure 1 concerns using behavioral distributions estimated from in vitro data to constrain the choice of parameters/tuples/object composition/etc. in an agent model -- model fitting. Phil seems to be talking about the situation where it isn't yet clear what to measure -- theory driving experiment, e.g. the development of general relativity preceding experiments to find gravitational waves. FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
Re: [FRIAM] FRIAM and causality
-BEGIN PGP SIGNED MESSAGE- Hash: SHA1 Phil Henshaw on 12/06/2007 10:53 AM: > The hard part seems to be to take the first dark step to accepting there > might be a shape of another form that the measures are missing (like the > whole tree or person). It means looking for how to best extend and > complete your image based on the limited cast of the measures at hand. > Interpolation gone wild?? Free form projection perhaps?? Sort of... > You just gotta do something to make sense of the larger continuities > that develop in natural complex systems. What I think we can see > clearly is that our measures and models are highly incomplete. I think we agree, which normally means there's nothing to talk about! [grin] But, I thought I'd throw out my term for what you're describing: "triangulation". It's not really triangulation, of course. But it's certainly more like triangulation than, say, population sampling. Perhaps we could call it "tuple-angulation"??? [grin] Here's a paper in which "we" (i.e. my outrageous rhetoric is reigned in and made coherent by the authors of the paper ;-) try to describe it: http://www.biomedcentral.com/1752-0509/1/14/abstract See Figure 1. This particular example is just one sub-type of the general method we're talking about, here, though. - -- glen e. p. ropella, 971-219-3846, http://tempusdictum.com If this were a dictatorship, it would be a heck of a lot easier, just so long as I'm the dictator. -- George W. Bush -BEGIN PGP SIGNATURE- Version: GnuPG v1.4.6 (GNU/Linux) Comment: Using GnuPG with Mozilla - http://enigmail.mozdev.org iD8DBQFHWX6LZeB+vOTnLkoRAhfiAJ4ldUf3p2wtlih3736TIp28uVtEZACfWyMf Pi/MX4iy1xD4PrqQNyNvbYo= =9GWs -END PGP SIGNATURE- FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
