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- Date: Tue, 5 Jan 1993 18:32:00 GMT
- Sender: "Control Systems Group Network (CSGnet)" <CSG-L@UIUCVMD.BITNET>
- From: Hortideas Publishing <0004972767@MCIMAIL.COM>
- Subject: The Devil Influenced Me to Do It
- Lines: 138
-
- From Dr. Diabolo, channeled by Greg Williams (920105)
-
- Note to Joe Lubin: MIND READINGS is $18 postpaid most anywhere.
-
- >Bill Powers (930104.0900)
-
- >Even trying to play Devil's Advocate pushes one into the
- >qualitative mode. Greg said that it is possible to detect the
- >disturbance through its effect on the cursor. That is true,
- >qualitativly. Everyone can tell immediately THAT there is a
- >disturbance, because the cursor doesn't behave as they expect it
- >to under the hypothesis that they have the sole means of
- >affecting it. But nobody can tell, on that qualitative basis
- >alone, WHAT THE DISTURBANCE IS.
-
- For the tracker to "respond" to the "discriminative stimuli," all that is
- necessary is for him/her to be able to see the cursor movement, NOT to
- "tell... WHAT THE DISTURBANCE IS." If the cursor is seen to be moving away
- from the target position -- due to the net COMBINATION of handle position and
- net disturbance, of course -- then the tracker responds by moving the handle
- in the direction (determined previously in practice, via "reinforced"
- learning) which moves the cursor in the direction toward the target position.
-
- >I should also point out that no matter what method a person uses,
- >there is no way of telling HOW MANY disturbing variables are
- >acting at the same time, or what their individual magnitudes and
- >directions are.
-
- Agreed. Only the net result of all disturbances AND handle position upon
- cursor movement is visible. If the net disturbance is zero and an
- inexperienced tracker "noisily" jerks the handle so that the cursor heads
- upward, the stimulus of solely-tracker-induced cursor movement will result in
- a response of change in handle velocity increasing in the direction which
- moves the cursor back toward the target. There might be overshoot, in which
- case the tracker responds again, appropriately. If the tracker is really
- "jumpy," there might be large continuing oscillations in the absence of any
- net disturbance. The degree of "jumpiness" or "smoothness" manifested by a
- tracker would be reflected in his/her personal stimulus-response functions.
-
- >Greg caught on to this in showing how, by looking at the
- >relationship between the handle and the cursor, the participant
- >could get more information about the disturbance.
-
- I didn't mean that the person is perceiving the handle position and using that
- to compute something about the disturbance. The person doesn't care where the
- handle is. He/she simply moves the handle away (in the "corrective" direction)
- from WHEREVER it is at a given time IF he/she sees the cursor move away from
- the target.
-
- If there are "noisy" functions relating "stimuli" and "responses" for
- practiced trackers, so be it. We demons admit that we need to add in random
- terms to our models of the PURELY EXTERNAL (TO THE ORGANISMS) FUNCTIONAL
- RELATIONSHIPS BETWEEN STIMULI AND RESPONSES. You PCTers boast about a high
- correlation between handle position and disturbance, but that glosses over the
- fact of irreducible noise in the stimulus-response functions. You simply
- integrate and the noise becomes less apparent. We, on the other hand, choose
- to tell it like it is: the tracker sees the cursor moving away from the target
- (under the influence of net disturbance AND handle position), and the tracker
- responds by changing -- with a pseudorandom component -- the velocity of the
- handle. If you like correlations, the integral of cursor velocity over time
- equals 0 equals the integral of handle velocity over time, but mere
- correlations don't identify "stimuli" and "responses." The record of handle
- position vs. time does not describe the true "responses" over the course of
- the experiment, it is only the RESULT of those responses. There is no
- necessity that the responses correlate well with the stimuli when noise is
- significant, since the responses tend to correct the "mistakes" of previous
- responses.
-
- -----
-
- Rick Marken (930104.1800)
-
- >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!!!
-
- Again, high correlations don't necessarily identify the real "stimuli" and
- "responses" when there is noise. The integration simply washes out the noise
- and leads the clever PCTer to get excited and say -- AH HA!! the INPUT-OUTPUT
- MODEL IS LOST!!! Of course, the inputs and outputs that got lost were those
- chosen by PCTers, not by us devils (and devilettes).
-
- >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.
-
- One last time: don't take high correlations as THE sign of stimulus-response
- relationships. Low correlations between stimuli and responses can result in
- "good-enough" performance of organisms over the long-run. (I.e., if there is a
- two-second constant lag between a light coming on and your throwing a switch
- that turns it off, and you want the light off, if the light comes on once
- every few minutes, over 24 hours it will be almost always off (nearly perfect
- correlation with the desired outcome), yet there will be zero correlation
- between the stimulus and the response each time the light comes on.)
-
- >>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).
-
- You should know us demons well enough by now to realize that we think trying
- to answer such questions is not important.
-
- -----
-
- Gary Cziko 920105.1523 GMT
-
- >Greg, have you gotten the Koza book on _Genetic Programming_ yet?
-
- No, not yet. I expect it this week.
-
- >It seems to me that this would be a nice problem for symbolic regression
- >(i.e., function identification) using genetic programming. You could
- >include all kinds of functions that you think could possibly relate the
- >output to the input and then let evolution do its stuff to find the magic
- >combination. If there is anyway to express the output as a function of the
- >input, it seems to me that genetic programming should be able to snuff it
- >out. These functions could involve time lags as well.
-
- And pseudorandom components, too, presumably. So the task for Koza is to come
- up with the function relating cursor position and velocity to handle velocity.
-
- Pat says that it might be appropriate to stress that velocity is a vector,
- including a specification of direction as well as speed.
-
- As ever,
-
- Greg
-