Archive for the ‘abduction (pattern extraction)’ Category

030828 – Are human beings rational?

Thursday, August 28th, 2003

030828 – Are human beings rational?

My wife asked an interesting question: Do I think that human beings are inherently rational.  I think the answer is emphatically no.  Human beings have the ability to learn procedures.  One of the procedures that human beings have discovered, found useful, and passed along culturally is the procedure of logical analysis or logical thinking.  The fact that in many cases logic enables us to find good solutions to certain classes of significant problems ensures that logical analysis will be one of the procedures activated as a candidate for execution in a broad range of external circumstances and internal states.

What strikes me is that the end result of evolution selecting organisms with greater and greater ability to learn and apply procedural patterns has resulted in an organism that is capable of learning to simulate serial computations, at least on a limited scale.  Certainly it was Dennett who put this idea into my mind, but I do not believe that he arrived at this conclusion by the same path that I did.

This raises an interesting question: what kind of pattern and procedural learning capabilities are required in order to be able to simulate serial computations or, more precisely, to be able to learn and execute a logical thinking pattern?  Human beings certainly aren’t much in the way of serial computers.  We’re not fast.  We’re not computationally adept.  We don’t have a lot of dynamic memory.  Our push down stack for recursion seems to be limited to one level.  (The fact that we must use the logical thinking pattern to analyze pathological sentences like, “The pearl the squirrel the girl hit bit split,” rather than the (unconscious) language understanding pattern simply underlines this limitation on our capability for recursion.)

So, is human language ability the result of the evolution of ever more sophisticated procedural pattern learning capabilities?  Is the driving force behind the evolution of such enhanced procedural pattern learning the advantage obtained by the organisms who best understand their conspecifics?  Is this evolution’s de facto recognition that brawn being equal, better brains confer a reproductive advantage?  Now if better understanding of one’s conspecifics is the goal, language ability may just fall out automatically, because if one has a mechanism that can build a model of others, it makes it a lot easier to figure out what the other intends or is responding to.

Clearly, since the ability to take the viewpoint of another person does not manifest itself in children until some time after they have acquired at least the rudiments of language, the manifestation of the ability to take the viewpoint of another person is not a requirement for the acquisition of at least the rudiments of the language.  There seems to be a subtle distinction to be made here: when daddy says “hudie” (the Chinese equivalent of “butterfly”) and looks at, or taps, or points to a butterfly or a representation of a butterfly, something has to help the child attend to both the butterfly instance and the sound.  That something may be the emerging model of the other.  Or maybe it’s the other way around as I suggested earlier: the trick is for the parent to take advantage of his or her own model of the child in order to intuitively construct or take advantage of the situation in which both the butterfly and the sound of the word will be salient to the child.

Still, I keep coming back to the idea that the internal model of the other is somehow crucial and the even more crucial is the idea that the internal model of the other contains the other’s model of others.  As I think about it though, it seems to me that creating an internal pattern, that is to say learning a pattern, based on experience and observation of the behavior of another organism is not a capability that is uniquely human.  It would seem to be a valuable ability to have.  What seems to be special about the patterns we humans develop of other people is that we attribute to the other a self.  An or to animal can get a long way without attributing a self (whatever that means) to other creatures with which it interacts.

030820 – The problem of brain design

Wednesday, August 20th, 2003

030820 – The problem of brain design

David Perkins, Professor of Education at the Harvard Graduate School of Education, observes (reported by Beth Potier in Harvard Gazette) ‘It’s far easier for a group of people to pool physical effort than it is for them to effectively combine their mental energy. He illustrates this point with what he calls the “lawn mower paradox”: 10 people with lawn mowers can handily mow a lawn much faster than one, yet it’s far more difficult for the same 10 people to design a lawn mower.

‘”Many physical tasks divide up into chunks very nicely,” he says, but not so with intellectual duties. “It’s pretty hard to say, ‘Let’s make a decision together: you take part A of the decision, I take part B of the decision.'”’

So what the brain has is a large number of interconnected pattern recognition systems.  The individual systems fall into a smaller number of categories, e.g., cortical systems, cerebellar systems, etc.  System categories differ among themselves at the very least in terms of plasticity and responsiveness to various neurotransmitters and neural activity modulators.

These systems each work along the lines proposed by Natschlaeger, Markram and Maass.  This is not to say that I totally buy into their liquid state machine model, but that I do believe that the systems act as an analog fading memory (with digital overtones) and that their structure serves to project their inputs non linearly into a high dimensional space.  Different systems have different memory decay time constants, ranging from short (early visual processing, for example), to medium (audio processing for speech recognition), to long (maintaining context while reading).

I hypothesize that (at least some of) these systems become tuned (and in that sense optimized) over time to their inputs (thus improving the separation of components projected into high dimensional space) by a process approximating Hebbian learning.  This could account for the acquisition of the ability to distinguish among phonemes when learning a language.  In effect, Hebbian learning creates “grooves” into which particular stimuli are likely to fall, thus enhancing the separation of minimally differing phonemes.

030728 – The simplest incomplete grammar

Monday, July 28th, 2003

030728 – The simplest incomplete grammar

If grammars are inherently incomplete, what is the simplest incomplete grammar?  Actually the question should be given an example based on say English of the simplest incomplete grammar.

Even if grammars are not inherently incomplete, one may argue that individuals acquire aspects of a grammar over time.  I vaguely recall that certain grammatical structures are in fact acquired at different ages as children learn languages.  Moreover, there are some built-in conflicts in the grammar of English (and probably just about any other language).  For example:

It’s me.  (Arguably based on the Norman French equivalent of modern French C’est moi).

It is I.  (Based on the rule that the verb to be takes the nominative case on both sides).

We’re truly unaccustomed to thinking about massively parallel computing.  Our approach to computing has been to create very fast single threaded processors; and as an afterthought, ordinarily to take advantage of idle time, we have introduced multi programming.  I think it is fair to say that our excursions into the realm of massively parallel computing are still in their infancy.  Without having done a careful survey of the literature, it would seem that the challenge of massively parallel computing  (at least that which would be patterned after neural structures in the mammalian brain) is to be able to handle the large number of interconnections found in the brain as well as the large number of projections from place to place.  [However, it is emphatically not the case that in the brain everything is connected directly to everything else.  It would be impractical, and it’s hard to see what it would accomplish beyond confusion.]

To hazard a gross oversimplification of the computational architecture of the brain, the brain is composed of layers of neurons, whose layers are identified by their common synaptic distance from some source of input.  Layers are stacked like layers in a cake (giving rise to “columns”, identified by their association with predecessor and postdecessor synapses.  To the extent the word “column” suggests a cylinder of roughly constant diameter, or even constant cross-section, it may be a bad choice of metaphor.  I imagine the diameter of a “column” to increase initially (as inputs pass deeper into the processor) and then to decrease (as signals that are to become outputs pass towards the effectors).  At various stages in the processing, intermediate outputs are transmitted to other areas (projections, via fiber bundles).  Depending on the stage of processing, a layer may receive synchronic input (that is, all inputs represent some class of inputs that originated at essentially the same moment in time, e.g., visual input from the retina) or, it may receive diachronic input (that is, a set of samples over time that originated at essentially the same location).  Indeed, some layers may receive both synchronic and diachronic inputs.

We don’t know much about how to think about the functions computed (computable) by such a system.  Not to mention that I don’t know much of anything about synaptic transmission.  Yeah, yeah, neurotransmitters pour into the synaptic gap.  Some of them are taken up by receptors on the axon and if enough of them arrive, the axon fires into the neuron.  But there are lots of different neurotransmitters.  Why?  How do the stellate glia affect the speed and nature of the pulses and slow potentials?  Do concentrations of neurotransmitters change globally?  Locally?

Somebody pointed out (Damasio?) that “homeostasis” is not really a good metaphor because the “set point” (my term) of the system changes depending on things.  In some cases, it’s clear what goes on: Too much water in the system?  Excrete water?  But the other side of that: Too much salt in the system?  Conserve water?  Well, yes, but what needs to happen is the triggering of an appetitive state that leads to locating a source of water (in some form, e.g., a water tap, a pond, a peach) and taking the appropriate steps to make that water internally available (e.g., get a glass, open the tap, fill the glass, drink the water; stick face in water, slurp it up; eat the peach).

At its core, this is a sort of low-level optimizer.  Based on the readings of a set of enteroceptors (sensors), create an internal state that either modifies the internal environment directly or that “motivates” (“activates”) behaviors that will indirectly modify the internal state.

It’s all very well to say that if one drips hypersaline solution into the CSF by the hypothalamus, the goat “gets thirsty and drinks lots of water,” but an awful lot has to happen on the way.

And it’s not very safe for the optimizer (governor?) to call for specific external behavior.  It can specify the goal state and monitor whether the organism is getting closer to or farther away from the goal state, but it’s not clear (with respect to thirst, say) how the information about getting closer to the goal can get to the optimizer at any time before an appropriate change in the internal environment is detected, e.g., the organism begins to ingest something that triggers the “incoming water” detectors.  Prior to that, it’s all promises.  Presumably, it goes something like this: behaviors “associated” with triggering the “incoming water” detectors are “primed”.  How?  Maybe by presentation of the feeling of thirst.  Priming of those behaviors triggers back-chained behaviors associated with the initiation of the “directly” primed behaviors.  And so on, like ripples in a pond.  The ever-widening circles of primed behaviors are looking for triggers that can be found in the current environment (more correctly, that can be found in the current internal environment as it represents the current external environment).

[Back-chaining seems related to abduction, the process of concocting hypotheses to account for observed circumstances.]

I keep coming around to this pattern matching paradigm as an explanation of all behavior.  It’s really a variation of innate releasing mechanisms and fixed action patterns.