# Martin-Tom: #1

**URL:** http://discourse.iapct.org/t/martin-tom-1/6790
**Category:** CSG1993
**Created:** [June 23, 1993, 3:45pm UTC](http://discourse.iapct.org/t/martin-tom-1/6790 "1993-06-23T15:45:45Z")
**Posts on this page:** 1
**Page:** 1

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### Author: ![Tom\_BOURBON3](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/t/85e7bf/32.png) [@Tom\_BOURBON3](http://discourse.iapct.org/u/Tom_BOURBON3)
#### Post date: [June 23, 1993, 3:45pm UTC](http://discourse.iapct.org/t/martin-tom-1/6790/1 "1993-06-23T15:45:45Z")

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> From Tom Bourbon (930623.0936)

Yesterday, I lost access to CSG-L for several hours. During that time,  
Martin Taylor and I pursued a direct discussion about information, plans and  
control. The discussion began on CSG-L asnd we thought we were still on  
the net, but were not. We agree that parts of our private discussion might  
be of interest to others following the threads on those topics;  
consequently, we will post the discussion. It will come in two  
installments -- Martin-Tom #1 and #2.

The discussion began on the net when I read a remark by Martin to Hans Bloom:

> **···**
>
> ================================  
> Subject: Re: Power gain, power loss.
> 
> [Martin Taylor 930621 11:10]  
> (Hans Blom 930619)
> 
> ..
> 
> On models, I tend to side with Hans. It is part of the whole information  
> argument. The more information is avaialble within the control system,  
> the less is to be acquired from the CEV through the perceptual apparatus,  
> and the better control can be.
> 
> ==================
> 
> > From Tom Bourbon (930621.1323)
> 
> > [Martin Taylor 930621 11:10]  
> > (Hans Blom 930619)
> 
> > Misunderstandings sometimes are better resolved by a non-combatant.
> 
> Most of Martin's post was about power gain in a control system. But at one  
> point Martin said:
> 
> > On models, I tend to side with Hans. It is part of the whole information  
> > argument. The more information is avaialble within the control system,  
> > the less is to be acquired from the CEV through the perceptual apparatus,  
> > and the better control can be.
> 
> Martin, to paraphrase a line from the movie, "Field of Dreams," all I can  
> say is, "If you build it, we will come." Take one example of  
> control, as it is recreated or predicted by PCT models, and show me, in the  
> results of simulations, how making more "information" available "within the  
> control system" improves the recreations and predictions from the model.  
> Then show me that those results generalize, with no further tinkering with  
> the model, to new conditions, with unpredictably different disturbances and  
> targets. That is not much to ask. Just improve on the performance of a  
> single-level, single-loop PCT model.
> 
> And please delineate how your ideas in the remark to Hans differ from, say,  
> a plan driven system that relies on information in the form of  
> programs for action, thereby freeing itself from a need to rely on  
> information about the CEV obtained through the pereptual apparatus. As you  
> stated it, I see no difference.
> 
> This is not a put down. It is the only way to do business, if you rely on  
> models to test your assumptions. It is my often repeated plea that you  
> present the evidence, in the form of improved performance of the PCT model.  
> Nothing else will impress us or win us over. You already know that. But  
> I assure you that, if you build it, we will come.
> 
> =====================================
> 
> Inadvertently, the next exchanges were private, starting from Martin:
> 
> ====================================
> 
> Subject: Re: Power gain, power loss.
> 
> [Martin Taylor 930621 18:00]  
> (Tom Bourbon 930621.1323)
> 
> > And please delineate how your ideas in the remark to Hans differ from, say,  
> > a plan driven system that relies on information in the form of  
> > programs for action, thereby freeing itself from a need to rely on  
> > information about the CEV obtained through the pereptual apparatus. As you  
> > stated it, I see no difference.
> 
> The difference is in those words "relies on" and "freeing itself from." I  
> have no concept of either. Change them to "uses" and "reduces its  
> need for" respectively, and I have less of a problem.
> 
> > Then show me that those results generalize, with no further tinkering with  
> > the model, to new conditions, with unpredictably different disturbances and  
> > targets.
> 
> What I assume would be in the model doesn't have much to do with the  
> disturbances and targets, but with what Bill has labelled f(e)--the  
> effect of a particular output change on the CEV. Reorganization is  
> one way of building a f(e) that conforms to a predetermined model, which  
> has the characteristic of being monotonic, as steep as can be constructed,  
> and leads to negative feedback. That "model" needs no explicit form.  
> It works with little information about the environment (which, Bill,  
> incorporates all the lower-level ECSs, not just the part of the world  
> outside the skin envelope) other than that the sign of the feedback is  
> constant and the environmental gain stays adequately high. Bats, on  
> the other hand, seem to adjust their perceptual input filters according  
> to the expected time and frequency of the (doppler-shifted) echo. They  
> need the model to distinguish the very low-power but precisely determined  
> echo from whatever else is going on in their acoustic world.
> 
> How could such a model work? In the neural-net world, one rather  
> powerful form of node is called a sigma-pi node. It does summation  
> and multiplication, and can be used as a variable filter. It would  
> be quite reasonable, I think, for a perceptual input function to contain  
> the pi part of the sigma-pi, in addition to the sigma that is generally  
> acknowledged to be there. The input to the pi could come from the  
> output signal, changing the relative sensitivity of different elements  
> of the PIF, and thereby changing its prior uncertainty about the expected  
> signal. That's just one way it could work.
> 
> I'm not committed (yet) to internal models in general. I can see their  
> potential usefulness, but they add a complexity to the ECS with which I am  
> not happy. In the syntax predictor that Allan is developing for me, we do  
> not include (yet) any internal model. We hope we will not need to include  
> one to achieve good prediction. We are starting by relying on perceptual  
> input functions that include differentiation. Nevertheless, when we  
> get to noisy, smoothly changing representations of the syntax, I am  
> at least open to the idea that we will have to incorporate models.
> 
> As I said, it's a question of the required information rate from  
> perceptual signals. If you are among those who consider it an  
> uninteresting quantity, you will not be interested in the possible  
> value of an internal model as a component of an ECS.
> 
> ==================
> 
> Here's a counter-challenge to the skilled modellers. I think it is fair,  
> because we have not yet developed our own model, so we can see whether  
> anyone, ourselves included, can solve the problem.
> 
> Define a formal grammar (say a BNF grammar) with 3 levels between the  
> root and the leaves. Assert for each leaf symbol a description consisting  
> of a location in an arbitrary 3-space (by analogy, think of phonetic  
> feature values for phonemes). Let a control system "see" the succession  
> of locations defined by the successive symbols output by executing the  
> grammar with predefined probabilities of taking the different branches.  
> The ouput of the control system is a location in 3-space. The three  
> "intrinsic variables" that the control system must maintain are the  
> difference between the locations of the output symbols and its own  
> three dimensional output. The control system may be designed or it  
> may learn (ours will learn).
> 
> Obviously, if the grammar output moves very slowly, any 3-D control  
> system will work. Our problem is to get the control system to move  
> to the right place as early as possible, preferably in synchrony with  
> the motion of the grammar output point, which is moving quickly.
> 
> So far, we have not defined a challenge grammar or specified its rate  
> of output, but we assume that the output point will have to stay stable  
> for at least two compute cycles for the control system to have any chance  
> of learning. We think that our control system will learn to have about  
> as many levels as there are in the grammar, but that remains to be seen  
> (it will grow by inserting ECSs between the "intrinsic variable" control  
> ECSs and the top perceptual layer, as discussed last week).
> 
> # =====================================
> 
> Subject: Re: Power gain, power loss.
> 
> > From Tom Bourbon (930622.1231)
> 
> > [Martin Taylor 930621 18:00]  
> > (Tom Bourbon 930621.1323)
> > 
> > > And please delineate how your ideas in the remark to Hans differ from, say,  
> > > a plan driven system that relies on information in the form of  
> > > programs for action, thereby freeing itself from a need to rely on  
> > > information about the CEV obtained through the pereptual apparatus. As you  
> > > stated it, I see no difference.
> > 
> > The difference is in those words "relies on" and "freeing itself from." I  
> > have no concept of either. Change them to "uses" and "reduces its  
> > need for" respectively, and I have less of a problem.
> 
> Fine. Change the words. Now, please because I still do not understand, tell  
> me how the model implied in your remarks to Hans differ from, say, a plan  
> driven system that "uses" information in the form of programs for action,  
> thereby "reducing its need for" information about the CEV obtained through  
> the perceptual apparatus. As you stated it, I see no difference.
> 
> > > Then show me that those results generalize, with no further tinkering with  
> > > the model, to new conditions, with unpredictably different disturbances and  
> > > targets.
> 
> > What I assume would be in the model doesn't have much to do with the  
> > disturbances and targets, but with what Bill has labelled f(e)--the  
> > effect of a particular output change on the CEV. Reorganization is  
> > one way of building a f(e) that conforms to a predetermined model, which  
> > has the characteristic of being monotonic, as steep as can be constructed,  
> > and leads to negative feedback. That "model" needs no explicit form.  
> > It works with little information about the environment (which, Bill,  
> > incorporates all the lower-level ECSs, not just the part of the world  
> > outside the skin envelope) other than that the sign of the feedback is  
> > constant and the environmental gain stays adequately high. Bats, on  
> > the other hand, seem to adjust their perceptual input filters according  
> > to the expected time and frequency of the (doppler-shifted) echo. They  
> > need the model to distinguish the very low-power but precisely determined  
> > echo from whatever else is going on in their acoustic world.
> > 
> > How could such a model work? In the neural-net world, one rather  
> > powerful form of node is called a sigma-pi node. It does summation  
> > and multiplication, and can be used as a variable filter. It would  
> > be quite reasonable, I think, for a perceptual input function to contain  
> > the pi part of the sigma-pi, in addition to the sigma that is generally  
> > acknowledged to be there. The input to the pi could come from the  
> > output signal, changing the relative sensitivity of different elements  
> > of the PIF, and thereby changing its prior uncertainty about the expected  
> > signal. That's just one way it could work.
> > 
> > I'm not committed (yet) to internal models in general. I can see their  
> > potential usefulness, but they add a complexity to the ECS with which I am  
> > not happy. In the syntax predictor that Allan is developing for me, we do  
> > not include (yet) any internal model. We hope we will not need to include  
> > one to achieve good prediction. We are starting by relying on perceptual  
> > input functions that include differentiation. Nevertheless, when we  
> > get to noisy, smoothly changing representations of the syntax, I am  
> > at least open to the idea that we will have to incorporate models.
> > 
> > As I said, it's a question of the required information rate from  
> > perceptual signals. If you are among those who consider it an  
> > uninteresting quantity, you will not be interested in the possible  
> > value of an internal model as a component of an ECS.
> 
> Please, all I asked was:
> 
> > > Then show me that those results generalize, with no further tinkering with  
> > > the model, to new conditions, with unpredictably different disturbances and  
> > > targets.
> 
> Of course, in the original I asked to see a generalization of the  
> results of simulations by the model you suggested. That is all I need to  
> see, for you to convince me that what you say about information theory  
> \*does\* translate into imnprovements in the performance of the PCT model.  
> In the demonstration, you are free (encouraged) to assume the model in its  
> fully developed and informed state. You need not simulate evolution,  
> conception, birth, maturation, learning, social control proceses, or  
> enlightenment. Simply take an extant PCT model, add to it the features or  
> measures you believe must be there for it to be an information theoretic PCT (IT  
> PCT)  
> model, and let it run. I described my criteria for improvement in other  
> posts long ago, and in one addressed to Hans Bloom a few minutes ago. A  
> demonstration like that would clear the air of gigabytes of "I said," "You  
> said," "We said," and the like. And it would focus the discussion on the  
> real issue -- does the PCT model work and, if so, can it be improved?
> 
> > Here's a counter-challenge to the skilled modellers. I think it is fair,  
> > because we have not yet developed our own model, so we can see whether  
> > anyone, ourselves included, can solve the problem.
> 
> This is another kind of "challenge" entirely. In fact, my offer is not a  
> challenge. I am merely saying that we know the PCT model works for certain  
> instances of control by humans. We know the model can be and should be  
> improved. We are eager to enlist the support of anyone who wishes to join  
> in that endeavour. The criteria for demonstrating improvement in the model  
> are simple and direct. Have at it. We have even published and posted the  
> PCT model (all two lines of it, if you include the environment) many times,  
> so you can avoid the need to develop your own model. Please, use ours as a  
> testbed for your ideas. (I am completely serious -- no attempt by me to be  
> cute, clever or condescending.)
> 
> This is not a contest in which we try to prove prowess and skill -- not for  
> me it isn't -- I have neither of those "attributes." My skills are limited.  
> I would like to see people with skills and resources superior to my own  
> devote some of their time and creativity to working on our project.
> 
> > Define a formal grammar (say a BNF grammar) with 3 levels between the  
> > root and the leaves. Assert for each leaf symbol a description consisting  
> > of a location in an arbitrary 3-space (by analogy, think of phonetic  
> > feature values for phonemes). Let a control system "see" the succession  
> > of locations defined by the successive symbols output by executing the  
> > grammar with predefined probabilities of taking the different branches.  
> > The ouput of the control system is a location in 3-space. The three  
> > "intrinsic variables" that the control system must maintain are the  
> > difference between the locations of the output symbols and its own  
> > three dimensional output. The control system may be designed or it  
> > may learn (ours will learn).
> > 
> > Obviously, if the grammar output moves very slowly, any 3-D control  
> > system will work. Our problem is to get the control system to move  
> > to the right place as early as possible, preferably in synchrony with  
> > the motion of the grammar output point, which is moving quickly.
> > 
> > So far, we have not defined a challenge grammar or specified its rate  
> > of output, but we assume that the output point will have to stay stable  
> > for at least two compute cycles for the control system to have any chance  
> > of learning. We think that our control system will learn to have about  
> > as many levels as there are in the grammar, but that remains to be seen  
> > (it will grow by inserting ECSs between the "intrinsic variable" control  
> > ECSs and the top perceptual layer, as discussed last week).
> 
> You got me there, Martin. Congratulations. I sure can't do that, but then  
> I never claimed to be a skilled modeler. Now, can I interest you in  
> helping us figure out how to improve the PCT model for something as mundane  
> and trivial as stick wiggling?
> 
> # =====================================
> 
> > From Martin Taylor, 22 June 1993
> 
> Subject: Re: Power gain, power loss.
> 
> Tom,
> 
> You responded to me personally, so I do the same. Did I mail to you,  
> rather than posting to CSG-L? I don't remember.
> 
> As I understand it, the problem with outflow plans is that they cannot  
> work because the world both is disturbed by influences unknown to the  
> pseudo-control system and because the impact of the output on the thing  
> to be "controlled" is not always the same. If the impact were defined  
> with high probability, and if the thing to be controlled were effectively  
> isolated from disturbance, outflow planning would work.
> 
> Do we agree so far?  
> ------------------------  
> [Tom -- present time -- 23 June]
> 
> Yes.  
> ------------------------  
> [Martin]
> 
> Now:
> 
> [Martin]
> 
> > > The difference is in those words "relies on" and "freeing itself from." I  
> > > have no concept of either. Change them to "uses" and "reduces its  
> > > need for" respectively, and I have less of a problem.
> 
> [Tom]
> 
> > Fine. Change the words. Now, please because I still do not understand, tell  
> > me how the model implied in your remarks to Hans differ from, say, a plan  
> > driven system that "uses" information in the form of programs for action,  
> > thereby "reducing its need for" information about the CEV obtained through  
> > the perceptual apparatus. As you stated it, I see no difference.
> 
> [Martin]  
> If you use "relies on" and "freeing itself from", you are talking about  
> a plan-driven outflow system. If you say "uses" and "reduces its need for"  
> you are talking about a normal control system that probabilistically  
> anticipates outputs that might affect the world usefully, but remains  
> based on the present difference between current perception and current  
> reference.
> 
> ----------------  
> [Tom - now]
> 
> I am not sure how a normal control system "probabilistically anticipates  
> outputs that might affect the world usefully," unless you mean something  
> like evaluating programs in imagination mode, then using one that seemed to  
> work sufficiently well in imagination. If that is the case, the program is  
> for perceptions, not actions, otherwise there is no difference between the  
> wordings you compared: there is not much difference, if any, between  
> "plan-driven outflow" and "outputs that might affect the world usefully."
> 
> ----------------------
> 
> [Tom, previously]
> 
> > Of course, in the original I asked to see a generalization of the  
> > results of simulations by the model you suggested. That is all I need to  
> > see, for you to convince me that what you say about information theory  
> > \*does\* translate into imnprovements in the performance of the PCT model.
> 
> [Martin]  
> You use the example of a sawtooth tracking task quite often in your  
> demonstrations. What do people do if after many cycles of the sawtooth  
> you stop the target at the mid-point and leave it there. Doesn't the  
> tracker overshoot before coming back to the target? But does the tracker  
> overshoot when the target reverses direction at the peaks of the sawtooth?  
> I think not, at least not after the first few cycles.
> 
> I haven't tried this, but here is a place where I make a prediction that  
> you have plenty of data to test. I am guessing that a simple ECS model  
> of one level tuned to a best fit to the human data will fail in two  
> specific places: (1) There will be a reversal in the sense of the  
> predictive miss at the peak between (a) the first one or two peaks, and  
> (b) peaks late in the sequence; (2) if you stop the target motion at a peak  
> after many tracking cycles, the human will reverse and come back, whereas  
> the model will not. The sawtooth should be fast enough that the human  
> tracks well, but measurably imperfectly.
> 
> Is this right?
> 
> ----------------------  
> [Tom -- now]
> 
> In examples I post on the net, I often use sawtooth targets, but only  
> because I can draw them in ASCII. I haven't figured out how to draw random  
> target paths. But since you mentioned them, events will occur as you  
> described them in the hypothetical demonstration -- if you stop the target,  
> the person will overshoot, then come back. (And will also reveal the  
> presence of other levels, by looking at you, or at the computer, and saying  
> things like, "it stopped working," or "what happened?")
> 
> However, the "overshoot" probably is not a result of "predictive movements."  
> The situation looks very much like the one described by Rick and Bill in  
> their chapter, "Levels of Intention in Behavior," in Wayne Hershberger's  
> book, \*Volitional Action: Conation and Control\*, (1989, North-Holland, for  
> those who do not know the book). What they studied, and what you describe,  
> is the result of differences in time constants for different levels in a  
> hierarchical control system. The "overshoot" you describe in the  
> demonstration, like that they describe in their chapter, occurs when for a  
> brief time a lower level system continues operating on the "old" reference  
> signal from above. It takes time for the higher level to detect error  
> which produces the new reference signal for the lower level. During the  
> time between onset of changes in the rules in the enviro\nment, and  
> alteration of the error signal qua reference signal from the higher level,  
> the lower level keeps on with the originally "correct," but now "incorrect,"  
> reference signal -- it keeps working perfectly.
> 
> -------------------------
> 
> [Martin]  
> I'm actually rather surprised to think that the "world-model" idea  
> might work at this low level. I had thought of it as being more  
> useful above the category level, and particularly at the program  
> level and above. But the theoretical background makes no such  
> distinction of levels, and if it actually does work as I presume,  
> the result should abort a lot of future fruitless discussion. The  
> question will (I hope) turn to how the world model information actually  
> is implemented in an ECS. Is it in the output function, the perceptual  
> input function, or (as I presume) in the imagination loop?
> 
> ----------------  
> [Tom -- now]  
> A world model (in imagination mode?) must affect the performance of the  
> system at \*every\* level, once the system begins to act on the model.  
> ----------------
> 
> [Martin]  
> As for the word "challenge," I agree with your comments. It is an ill-chosen  
> word. However, much of what has been going on has the flavour of challenge,  
> and the word came quite naturally. I would be much happier if it didn't.  
> And I'm not the modeller. That's not my skill, either. I'm more of a  
> theoretician (as you doubtless have observed). Allan is doing the work.
> 
> # =======================
> 
> [Tom -- now]
> 
> Fine! I like the idea of cooperation or collaboration, perhaps with a  
> bit of heat to liven things up, better than challenges. (Care for a round  
> of stick wiggling?)
> 
> That has us almost caught up. I will send a few of today's posts a little  
> later.
> 
> Until later,  
> &nbsp;&nbsp;Tom Bourbon