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- Posted-Date: Mon, 04 Jan 93 19:26:10 PST
- Message-ID: <199301050326.AA01900@aerospace.aero.org>
- Newsgroups: bit.listserv.csg-l
- Date: Mon, 4 Jan 1993 19:26:10 PST
- Sender: "Control Systems Group Network (CSGnet)" <CSG-L@UIUCVMD.BITNET>
- From: marken@AERO.ORG
- Subject: devil's advocacy
- Lines: 86
-
- [From Rick Marken (930104.1800)]
-
- Greg Williams (920103 - 2)--
-
- >It will not amaze those who think PCTers have identified incorrect "stimuli"
- >and "responses."
-
- In a compensatory tracking task all the subject can see is the time
- trace of the cursor -- c(t). In the "different stimuli/same responses"
- experiment there are two "stimuli" -- c1(t) and c2(t); the output is
- the traces, o1(t) and o2(t), which are the same to c1(t) and c2(t),
- even though the stimulus traces are different each time. If the
- outputs were proportional to some non-linear function of the inputs
- then c1(t) and c2(t) would be the same -- we would not know the nature of
- the function, just that some function would work; but, since c1(t)<>c2(t)
- there is no need to look for such a function. The same is true for the
- possibility that the output is based on a delay with respect to
- c(t) -- for example, o(t) = f(o(t-tau)); but this possibility is
- rejected by the result as well -- since the same delay would
- characterize the response to both c1(t) and c2(t) so c1(t) should
- equal c2(t) -- but they don't. So the "different stimuli/same
- responses" experiment shows that the lack of correlation between
- cursor (c(t)) and output (o(t)) in Bill's experiment is NOT because
- o(t) = f(c(t)) but f is highly non-linear and it is not because
- o(t) = f(c(t-tau)).
-
- The experiment does NOT rule out the possibility that there may be
- a relationship between derivatives or integrals of c1(t) and c2(t)
- and, indeed, if you compute the indefinite integral of the cursor
- traces -- call it int(c(t)) -- you DO find a correlation between
- the integrals -- and there IS a high correlation between
- int(c1(t)) and o1(t), for example. So now the clever nonPCTer
- can get excited and say -- AH HA!! int(c1(t)) IS THE STIMULUS
- that guides responses in a tracking task -- the INPUT-OUTPUT
- MODEL IS SAVED!!!
-
- This is where quantitative modelling is needed again (one little
- demo can't shut the non-PCTer up forever -- if at all). If int(c(t))
- is the stimulus for tracking then we should be able to build a
- model using int(c(t)) as the stimulus. I did this -- I have not been
- able to make the model work. Maybe I havn't tried hard enough. The
- model I used is as follows
-
- c(t) = o(t) + d (t) ; cursor position at any instant depends on
- the output (handle position) and the disturbance
- (this is just a physical fact).
-
- p (t) = int (c(t)) ; the stimulus (perception) that causes the response
- is the indefinite integral of cursor position
- (where cursor position is measured relative to
- the target, which is 0).
-
- o (t) = -k* p(t) ; the input-output equation; handle output is
- proportional to perceptual input (k is negative
- because the correlation between int(c(t)) and
- o(t) is negative -- because it's a negative
- feedback loop.
-
- One can diddle with k to try to make the model work. I couldn't make
- it work. I also tried making the integration "leaky"; this didn't
- work either. I would prefer an analytic proof that the integral of
- cursor position cannot be the "stimulus" for control -- but I can't
- do it; this would be a nice job for a real mathematician.
-
- So why does int(c(t)) correlate so highly with o(t); because the output
- of the control system is int(c(t)) -- generated in a closed loop; the
- integral is picking up the component of c(t) that is the result of o(t) --
- remember c(t) = o(t) + d(t) -- and in a control loop o(t) is the result
- of an integration of the error signal (I think this is the explanation,
- anyway).
-
- >Where is the person who is claiming that there is ONE function which maps all
- >of the different i's to the same o? They will say that each i has a different
- >function mapping to the same o, which is perfectly possible, mathematically.
-
- Then I hope they will also say HOW the system knows which function to
- pick each time in order to map the different c(t)'s into the same o(t).
-
- >It looks as though they might contest PCTers' claims QUANTITATIVELY, too. It
- >all hinges on their claim that your i and o are straw variables.
-
- I think it all hinges on what they mean by QUANTITATIVELY.
-
- Best
-
- Rick
-