Syntax and robot behavior

I think the difference is that humans have the ability to manipulate
private state that is independent of the environment to an extent that is
far beyond all other animals.  Before we can develop language to talk about
what happened yesterday, we first have to remember what happened yesterday,
or what happened 10 minutes ago.  By this, I mean we have the power to call
up memories of the past.  When we do that, all that I think is happening is
that our brain is partially activating old states, created from experience.

So, when sensory data flows in, it's decoded through a large parallel
network which specifies how the current sensory signals are different from
other sensory signals as well as decoded all the way to the correct actions
to take in response to this current sensory environment.

If we see/sense 100 things that are around us, it's because there are 100
different parts of the network activating at the same time in response to
this current sensory environment.  I know there is a computer in front of
me only because parts of by brain that represent that idea have been
activated in response to this visual data.  But at the same time, many
other lower level parts of the brain are being activated by the vision data
- the parts that detect simple edges, and areas of color, and shapes.  It's
all this combined that creates our full experience of seeing a computer.

All that "state" is activated directly by our current and recent past
sensory inputs and all that state is also driving our behavior.

But, humans also have the ability to active some of that network state,
independent of the current sensory inputs.  We can create a memory of
something that happened in the past by making part of that network activate
again.  I can close my eyes, and still "think" about looking at the
computer.  This memory is very weak and poor compared to the sensation of
actually seeing a computer because only a very small part of my brain is
being put back into that "seeing a computer" state when I have the memory.

If I remember seeing a snake yesterday, it's because my brain has sections
which are able to disconnect from the current sensory experience.  It's
hard for example, for me to look at my computer screen, and have a past
memory of seeing a snake at the same time.  I almost have to close my eyes
or at least, concentrate to block the sensory data in order to allow me to
have a past memory of seeing a snake.  This is because the current sensory
data is trying to force the brain into the configuration of looking at a
computer monitor.

None the less, humans have a lot of power to do things like close our eyes,
and make our mind drift back to partial (very partial) recreations of past
experiences.

Our behavior however is a function of the entire state of the brain.  So,
when parts of our brains are recreating state from past experience, our
behavior can also be a function of that part of our brain state, instead of
being a function of only brain state created from current sensory
experience.  In other words, we can produce behaviors that are function of
our memories.  We can say something like, "hey, that snake is like the one
I saw yesterday".  That's because when we first saw the new snake, a small
part of the brain switched back to a state that represented what happened
yesterday.  But not all of it switched back (not very much of it at all
really) which is why we can for the most part not be confused about what is
happening now and what is a memory.  We only get confused about that if we
cut off our sensory inputs so that the memories are all we have to react to
- like what happens when we sleep and dream.

I think animals have nearly as much state information in their brain as we
do.  It's just that most of their state is always a direct connection of
the current sensory inputs.  Most of our state works that way as well.
It's how we know where we are and whats going on around us.  But because we
have this percentage of the brain that flaps in the wind and can flip back
to old states it allows us to react now, as if we were reacting to
something that happened last week.

So I don't think we have that much more state.  Or that we can can react in
ways all that more complex than the ways many higher animals can react to
their internal state, I just think that for some reason, some sections of
our brain has a bit more freedom to disconnect from current sensory inputs,
and switch to active configurations which represent states that were active
in the past.  We constantly have memories of past events which allow us to
act in complex ways that many animals don't seem to have.  Most of them
seem to be far more forced to react to only what is happening around them
instead of having a brain that can switch to a past experience (aka
daydream).

A dog for example shows clear signs of action that shows their behavior was
based on past experience.  They run to the door to be let out because they
know that door is how they are let out.  But this doesn't seem to happen
because they can recall a past memory of being let out that door.  It seems
to happen simply by conditioning.  I don't see any real signs of dogs day
dreaming.  They only seem to react directly to what's happening around them
(except when they are sleeping and they do seem to have dreams in that case
but that's easy to explain if your body cuts off your sensory signals and
lets the brain free-wheel).

--
Curt Welch                                            http://CurtWelch.Com/
curt@kcwc.com                                        http://NewsReader.Com/

Yes to all you've said, except I interpret it differently.

I describe it by saying that we have an additional sense, a
"sense of thought". That is, we can perceive our own thoughts
at a sensory level, and process them through the lower brain's
sensor fusion circuits without losing track of the fact that
what we sensed actually originated internally - just as we don't
lose the fact that what we just saw was a sight, not a sound.

I think this idea can be used as a basis for explaining most of
what we observe as consciousness, dreaming (including day-
dreaming), etc, and probably very many disfunctions also, such
as autism, bipolar disorders, etc.

I mention autism because if the sensory origin of each percept
is lost during sensor fusion, then the ability to distinguish
internal from external senses is lost, and internal disturbances
can create instability in the apparent "real world", leading to
profound disorientation. I would expect behaviours on the order
of those encountered in autism to be the result.

Clifford Heath.

Yes, I've used that exact idea many times in trying to explain (and
understand) what thought is.  I strongly try to argue the point that we
sense our thoughts just like we sense the external world.


But here's where it gets interesting.

Just where in the brain does "sensing" start and stop, and where does it
turn into something else?  And what else does it turn into after it stops
being sensing?  I think the entire path from sensor to effector is doing
"sensing".  I even argue that every neuron in the brain is acting as a
sensor.  But instead of sensing light, or heat, or pressure, most are
sensing temporal patterns of neural activity in other neurons.  Most the
neurons in our brain are in fact, "brain activity sensors".  With a head
full of brain activity sensors, is it surprising that we can sense our own
thoughts? :)

I used to think of my brain the same way I thought about a piece of
electronic equipment like an audio amplifier connected to a microphone and
speaker.  The sound that it senses exists at the microphone, and is
recreated at the speaker, but that in the middle, there was just "magic"
that represent the sound using electrons.  The sound didn't exist inside
the machine.  The amplifier "sensed" the sound, only at the microphone.
That was where sensing happened in a system like that.

Likewise, I felt that I sensed with my eyes and ears.  I felt that the
processing that then happened inside the brain, was all invisible to me -
it was all just part of the magic of the subconscious.  When I see a dog, I
was seeing it with my eyes.  When I hear a dog, I was hearing it with my
ears (as we normally talk about these things).

But, after more thought on this is problem, I realized that can't be how it
works at all.  This is because as the data from the eyes is processed
though higher levels of the brain, the neural circuits are responding to
higher level abstractions - to higher level meaning in the data.  The cones
in the eyes, only see brightness, or lightness, at one spot.  Further
along, we have neurons that "see" center surround features.  Further along,
there are neurons that "see" edges.  Way further alone, there are
collections of neurons that "see" the dog.  It's not the eyes, or the first
N layers of processing that "sees" the dog, it's only the higher level
circuits that can see a dog.  And they "see" it by becoming active when the
sensory data contains the correct type of dog pattern.  They dog detection
circuits in our brain are not seeing the light, they are seeing the "dog"
in the firing patterns of other neurons.

We see how this can turn off, and on, when given optical illusions that are
so distorted they are hard for our brain to find patterns in.  Such as the
classic dalmatian dog in the middle of a picture full of back and white
shadows.  The first time you see the picture, you don't see the dog.  But
at some point, you find enough clues, and suddenly, the dog jumps out at
us.  The picture before we saw the dog is what the lower level detection
hardware as able to make out (mostly just odd meaningless white and black
spots).  But then suddenly, the "dog" detector found enough patterns to
work with, and started to fire.  Every thing we understand about what we
see, and hear, and feel, is due to the fact that there are neurons firing
in our brain that represents that understanding. It's all just brain
activity.

In other words, what this implies, is that our conscious awareness, aka,
what we are constantly aware of, is all the neural activity happening in
our brain.  It's not the microphone, or the eyes, that's doing the real
sensing work at all, it's a head full of neural activity detectors that
allow us to have this complete understanding of what's happening around us.

But, where does this job of sensing stop, and the job of acting begin?  Is
one part of the brain used for sensing, where all our awareness is
generated?  The only real option would be the sensory cortex vs the motor
cortex.  But I strongly suspect the motor cortex is nothing more than a
sensory cortex, wired up to sense our own behavior - to sense the outputs
of the brain.  So if we have conscious awareness of all the "magic"
happening in the sensory cortex, we should have conscious awareness of all
that is happening in the motor cortex as well.  In other words, the entire
information processing path, from sensor, to effector, is our conscious
awareness - none of it is hidden to us.

So, this implies, that the processing happening in the brain is not hidden
magic like what happens inside some piece of electronics.  This implies
that everything we are aware of, is what is happening in our brain, and
that nothing else is happening in there (at least not in the path that
connects sensors to effectors and forms this major feedback loop through
the environment).  What we are not aware of, is the low level chemical and
biological processes at work which are busy re-wiring our brain - adjusting
weights, adding neurons, etc.  The data flowing in the brain, is what we
are aware of.

So, when I look around the office and see all the stuff, it's not the
office I'm sensing as much as it's the brain activity that I'm sensing.
The stuff in my office is what caused these patterns of neural activity to
form in my brain, but what I'm aware of, is the neural activity, not the
office itself.  So like looking at a TV screen and seeing people, but
knowing in fact I'll I'm seeing is flashing red, blue, and green dots on
the screen, I now look around the office, and know that what I'm seeing, is
not a office full of stuff, but just the flashing of billions of neurons.

So with all that as background, let me repeat what you wrote above:


I don't think we have "lower level" sensory fusion circuits.  I think the
whole thing is sensory fusion circuits.  The fusion happens at all levels.
When a center surround detector activates because of the correct pattern of
light levels in a small collections of cones, it is doing fusion.  It's the
same fusion that happens at all levels.  The neurons are detecting temporal
patterns of activity in other neurons, and in doing so, they "fuse" the
information in those other neurons, into a new piece of information.  A dog
detector neuron fuses activity from other lower level detectors, which had
previously fused activity from detectors below that.

We see the dog, because the dog neuron (or neurons) activate.  We see his
spots at the same time, because there are "spot" detectors activating at
the same time.  We see 3 of his legs, and 1 ear, because 3 "dog leg"
detectors, and 1 dog ear detector has also activated.  The entire sensation
of seeing a dog, in a particular position, is the sum total of the
activation of all these detectors at once.

But what happens if later, the "dog" detectors activate, but there are no
"dog leg" detectors active, or "dog ear" detectors active, or "dog spot"
detectors active?  This is the sensation we have of "a thought about a
dog".  What the thought is "about" is controlled simply by which high level
detectors have been activated.

How do we tell a memory of a dog from the sensation of seeing a real dog?
Simply by the fact that all the lower level detectors are not active at the
same time.  We no doubt have many different types of "dog" concepts all
associated with different detection circuits in the cortex.  The type of
"dog" thought we are having is created by different combinations of these
detectors.

So, I agree with your idea that we are sensing our own internal thoughts.
But I don't believe it works because there is something feeding back brain
activity, to our lower level sensory circuits.  I think it's just a natural
process of what the entire brain is doing.  It's translating sensory data,
into effector data, and all the middle terms of this translation is what
makes up our "awareness".  There are "dog" signals in the middle of this
translation simply because it was helpful for the brain to create these
signals on it's way to creating the signal that controls our arms and legs.


Yes, as a matter of fact, I've used the position that we are sensing our
thoughts to explain in a mechanical way both what conscious is, and why
there is this pervasive myth in all cultures that the mind is separate from
the body.  I think it's the only correct way to understand our thougths.


I don't understand autism enough to know much, but I've wondered about
these sort of things as well.  A model which correctly explains brain
function should also be able to explain all the Brian dis-functions.  The
brain dis-functions should act as strong clues about the structure of the
brain - if we only knew how to read the clues.

If a lack of connection to reality is a symptom though, the issue could be
explained by a brain which is configured to be less sensitive to current
sensory inputs, and more free to flap in the wind and generate it's on
memories and thoughts - more like a person constantly daydreaming and only
slightly connected to reality.


--
Curt Welch                                            http://CurtWelch.Com/
curt@kcwc.com                                        http://NewsReader.Com/

Yes... but that tends to imply a single amorphous massively-
connected network, and that's clearly not what brains are.
They do exist in clumps, layers, clusters of neurons having
both local and distant communication channels, but local
circuits predominate. Current theory is that there is a form
of voting going on in sub-oscillatory circuits based on
particular distances (loop-lengths, which relate to time-
delays) being typical of each individual site. I.e. a certain
cortical surface may be populated by neurons having most
synapses almost exactly 3.2mm away, where other areas of the
brain have other distances. The brain decides what it's
sensing by the circuits forming reinforcement patterns that
cause a particular pattern in that area, like when a player
at Risk fights back and forth and eventually wins a continent.


Yes, possibly, but not all of the brain is contributing to all
of the activity - the brain is not amorphous. The morphology has
been extensively studied and related to particular sensations
and activities, and there are clearly zones that correlate between
individuals. There is also strong evidence that core structures
from the cerebellum up relate to evolutionary phases - we have a
reptilian brain, a mammalian brain wrapped around that, and a
human brain in the morphology and function of the cortex. Many of
the functions e.g. of the mammalian brain (mothering, emotion,
etc) can be observed in all mammals, but not in reptiles... so
these functions are clearly arbited within these structures not
the older ones. Though all parts of the brain might be involved,
the functions only emerge when these higher structures are intact.

In regard to sensory fusion, it's very interesting to read studies
on synaesthesia. In this condition, senses cross over - so a taste
might be sensed as a texture ("there are too many points on the
chicken stew"), or a sight might evoke a colour. By mapping the
dimensions of the senses reported, it's possible to learn about
the kinds of sensory processing occurring on individual senses
before the sensations are fused. I figured out some of this stuff
after reading "The Man Who Tasted Shapes" - look it up.

However, the upshot is that though we form a particular concept
like "dog" at some level, the sensory origins are not lost in the
fusion process. That means that each concept is associated with the
activities (or at least the level of involvement) of the individual
senses involved, so we can normally tell what part of our thought
is imaginary. My theory is that we can inject hypothetical
sensations in to the middling stages of sensory fusion, while
retaining the ability to determine that the outcome of fusion has
been affected by the injection. It's this ability to distinguish
internal sensations from external ones that we call consciousness.

The evolutionary driver for it is that being able to conjure up
hypothetical situations improves our ability to predict. We can
run "what if" scenarios in more complex ways than lower animals.
A hunting cat might have learnt that to stalk prey from behind
cover is better, but it still has to look here and there to decide
where the cover is best - that's a "what-if" scenario. Humans are
just better at it. Prediction is the core of intelligence. It's
also the core of our enjoyment of company, humour and music. We
have a biological imperative to improve our ability to predict,
in order to eat instead of being eaten.

BTW, the study of information theory and in particular data
compression is absolutely key to understanding what's going on
and how to reproduce it artificially. Compression is the art
of removing whatever is predictable in an information stream.
I've wondered if it would be feasible to build a type of robotic
cerebellum using a small micro with large data compression tables
to create learning behaviour like our muscle memory. Like Asimo's
taught strides, but learnt instead.

 >  Is

No. But remember - the cortex is only the couple of millimetres of
the outer skin of the brain. Most of the kilojoules are burnt there,
but the rest of the brain volume is also active, it's not just a
backplane.


Well that's demonstrably wrong (reflexes and muscle memory aren't
subject to direct perception and control), but I see where you're
trying to go with it.


That theory offers no explanation of synaesthesia, for example.


That's true - but there is still a stage where a sound, or a sight,
is still an isolated phenomenon, not yet joined into a single concept.
That's a lower level, and AFAIK, not one into which we can inject
a hypothetical sensation. At some point, the sensations are related
to each other, unified into a single concept, and it's likely there
that we can inject our "sense of thought". The circularity of this
causes pulsing oscillations of activity which we identify as thought
and can measure on ECG's - they're brainwaves.


I think you contradicted yourself pretty thoroughly there. It might not
be accurate to talk of "levels" of processing, since there is a clear
circularity, but there is clearly localization of certain *kinds* of
processing. Not all areas are accessible to direct perception.

Clifford Heath.

This is very likely where Brooks' idea of the subsumption architecture
originally came from. Newly-evolved areas subsuming functions of
ancient structures.



That sounds like one of Oliver Sacks' essays. You might also check out
V.S. Ramachandran's book, A Brief Tour of Human Consciousness, 2003,
which also talks about synesthesia. His evidence indicates that
synesthesia may be due to incoming sensory fibers which inadevertently
spread migrate from their proper termination areas of [usually
temporal] cortex into nearby areas, which process a different sensory
modality.

http://en.wikipedia.org/wiki/Vilayanur_S._Ramachandran

"... Ramachandran suggested that synesthesia may arise from a similar
cross-activation between brain regions. However, rather than being
within a single sensory stream, this form of cross-activtion would
occur between sensory streams, and is thought to be due to genetic
differences, rather than neural re-organization..."



This is no doubt based on the fact there is topographic [spatial]
mapping from senses to cortex in all modalities, and all later-on
processing uses these maps as the "primary" reference point.




"taught strides" ??



Curt's comments seem to imply there is no such thing as subconscious
processing, whereas it's commonly accepted that maybe 99% [whatever] of
brain processing occurs subconsciously, below our awareness level.

It's just an issue of what parts create the "subconscious".  That's a big
part of the point I was getting at in the post.  Where as I had assumed for
a long time that a lot of the neural signals in the neocortex was part of
the "magic subconscious" that made everything work, I now believe it's more
likely that the firing of the neurons, and the signals the spike codes
represent, are the consciousness we are aware of.  The underlying
mechanisms that regulate when the neurons fire, and which rewire or adjust
the connection strengths between the neurons is the subconscious process we
are not aware of.  That is, when a synaptic strength changes, we are not
consciously aware of that change.  But when the neuron ends up firing
later, when it wouldn't have otherwise, which then triggers a chain of
activity in other neurons - that's what we are consciously aware of.

But notice I'm not talking about the entire brain and every neuron the
fires. I'm only talking about those neurons (mostly in the neocortex) which
are part of that direct signal path that connects sensory inputs to
effector outputs and all the loops in that path.

--
Curt Welch                                            http://CurtWelch.Com/
curt@kcwc.com                                        http://NewsReader.Com/

Oh yes, those direct paths. What do you suppose the neurons stuck in
indirect paths are up to?

--
Joe Legris

Well, I think the neocortex is first and foremost, a reinforcement learning
machine.  So in addition to the cortex which is the reaction machine that
is trained through experience, there must be critic hardware which is the
hard-coded circuits needed to generate the reward and punishment signals
which shape the behavior of the neocortex.  So that's part of the hardware
I would expect to find in the mid brain for example.  It's support circuits
for the cortex.

Second, I suspect the reinforcement learning cortex was added on top of a
system of hard-coded instinctual behaviors which was a much older part of
the brain before it developed these strong general learning abilities.  So
some large section of the lower brain is most likely hard coded instincts
which the learning part has the power to override.  This is very important
in most animals which must be able to survive on the own within minutes of
birth, but has been nearly completely replaced by learned skills in humans
who have the luxury of a very long learning period (years) before they have
to develop all the skills for survival.

Next, much of the lower brain is no doubt there to help regulate important
body functions, such as keeping the heart beating, controlling breathing to
some extent, helping to control and regulate the digestion process, helping
to regulate various chemical levels in the body, etc. - all that stuff that
was needed to keep a complex organism alive before it developed these
strong general learning skills.

The cerebellum is another major chunk of brain which is not a direct part
of the main reinforcement learning system that I think creates our
conscious awareness and intelligence.  It seems to be some type of output
motor processor which acts much like PID controllers act in our robots to
help make the body parts respond proportionally to what the signals
represent instead of having to build in the physics and reaction
characteristics of each body part into the higher level controls.

--
Curt Welch                                            http://CurtWelch.Com/
curt@kcwc.com                                        http://NewsReader.Com/

This is kind of the cortex = tabula rasa argument, but might not be so
cut and dried as you indicate, since animals such as horses, which can
get up and run and follow their mothers within a few minutes of birth,
also have neocortex. Hard to imagine the cortex is doing nothing for
the colt in early life, because it hasn't learned anything as yet.

Rather than contending all of this "instinctual" colt-early-life stuff
takes place below the cortical level, and that the cortex is mainly
just for reinforcement learning, it's much more likely the cortex has
added many advanced processing capabilities on top of the older areas,
but also the ability to modify those capabilities to a much greater
extent than can happen in sub-cortical levels. IOW, the "general"
functions of the 30+ cortical visual areas, as well as their
interconnections with the rest of the brain, are actually determined in
the genome, rather than learned after birth.

Yeah, that's the stuff that more research needs to answer.

Of course, the neocortex has been receiving signals and "learning" for a
long time before birth, so it's not exactly "blank" when the horse is born.


It's possible.  Research is needed to answer these questions.

Much of the bulk configuration of the neocortex is clearly predefined in
the genome.  But how much of the interconnections that develop happen after
the eyes start sending data to the cortex?  I don't know when the eyes form
and first start to send signals, but I know it's long before birth.  If we
could just cut up, dissect, and stick probes in a few thousand human babies
we could answer more of these questions. :)

Without knowing the answer, we still have the issue of what we can do as
programmers and robot builders to push the technology forward while we wait
for the neuroscience to figure out more about real brains.

I believe there is still much to be learned about generic signal processing
and learning systems.  The type of system you can feed any sensory signal
to, and it will figure out on it's own, what to do with the sensory
information.  I happen to believe the neocortex and most the supporting
structure is just such a module in the brain, but whether I'm write or
wrong about that is not all that important.  What's important is whether
there are better generic learning algorithms still possible to be
developed.  I think they are (and I think it's the key to creating human
like behavior in robots), so that's what I'm exploring.

If your think the cortex is instead a lot of custom designed circuits, each
for dealing with it's own special type of sensory data, then you can go
about trying to duplicate such algorithms in code for processing data such
as video.  It's wise for people to be working on both approaches to see
what we can find.

--
Curt Welch                                            http://CurtWelch.Com/
curt@kcwc.com                                        http://NewsReader.Com/

It's what the neocortex is and that's mostly what I was making reference to
even if I didn't make that clear.  The lower, and older brain is mostly not
part of the path from sensor to effector output.


The neocortex is mapped rather well into many different areas (I think Dan
likes to quote something like 21 visual areas?).  But it's not mapped by
it's physical structure as the rest of the brain is - it's mapped only by
the nature of the signals being carried in each section - just as we would
have to map computer memory.  The neocortex, like computer memory, is a
single amorphous massively-connected network - well not exactly because
there are distinct pathways between different cortical sections but the
entire neocortex is made up of the same fundamental hardware structure just
like computer memory is all made up the same fundamental hardware structure
grouped into modules with pathways between them.


There are many current theories but few actual answers. :)


Are you talking about the diameters of the interconnects for superficial
pyramidal neurons?  Yes, it's clear that evolution has tuned their design
to optimize the structure in different sections of the neocortex, and from
species to species they are different.  But still, the entire neocortex is
basically the same structure - micro columns combined to form macro columns
combined to form various cortical regions.


Yeah, the cortex definitely forms networks which seem to want to lock into
different stable states - Walter Freeman's work seems to come up a lot when
people talk about the connection to chaos theory and strange attractors in
how the brain's state seems to lock onto various stable points.

The basic behavior of the brain tending to lock into a stable state is
easily demonstrated with optical illusions that our placed between two
stable interpretations such as the goblet that looks like two faces.  We
can make our brain jump from one to the other but once it's changed, it
wants to lock onto the interpretation and block the other.

This tendency is also easily understood by looking at the cortex as a
pattern recognizer which uses feedback to lower levels to improve the
accuracy of the interpretation.  Once the higher level circuits see a "dog"
in the picture, that information seems to be feed back to lower levels to
allow us to see something like a dog-ear which we would never had
interpreted as a dog-ear had we not first recognized the larger image to be
a dog.  Once you add feedback of that type, the system will naturally want
to "lock" into a stable configuration (the one created by "I see a dog and
lots of dog parts").

But still, it's not the the fact that the brain has locked into a stable
configuration that means "dog+dog parts".  It's the actual neurons that
fire which seem to represent what we are sensing.  When the brain is locked
in to the "dog" pattern there will be a different set of neurons activated
then when it's locked into a "cat" pattern.


Yes exactly. There are zones that represent different colors, and zones for
faces, and zones for sounds.  Each neuron or small cluster of neurons (like
a cortical micro column) seems to have a precise "meaning" to our conscious
awareness.  We only sense that "meaning" when those neurons are active.
Our total conscious awareness at any one time is then, most likely, simply
a function of which cortical columns are currently active.

At the same time, these neurons can be activated artificially and in doing
so, people report they are able to sense some conscious awareness connected
to the stimulation.   I don't know how extensive this type of testing has
been to try and get a better map between activity and conscious awareness.
I suspect it's considered too dangerous to do much of with humans so I
suspect the testing has been limited mostly to cases where brain surgery
was needed for other reasons.


Right, I'm only really interested in the neocortex.  The rest for the most
part doesn't seem to be very relevant to AI - it has more to do with
keeping us alive than in making us intelligent.


I've not seen much on that.


I'll keep it in mind.

One of the biggest mysteries of the brain is trying to understand why each
of our sensory experiences seem to have such a unique, and different
sensation.  Why does red look red to us for example?  The neurons that
define redness for us are not any different than the neurons that define
blue for us.  So why do we end up with such different perceptions of these
signals?

The answer I like is that our perception of all the senses is simply
created by how they all relate to one another in the brain - in how they
are associated and in the behaviors they tend to create in us.  This is a
fairly weak answer, but it's the only one that makes sense to me.

This would imply that sounds should always sound like sounds, and not
invoke a color sensation.  The only way I believe that could happen, is if
the color sensation was formed by mostly processing visual data in the
correct way, but then having a cross connect from the auditory data into
the color sections that could also, at times, simulate a similar pattern.
In other words, a slight, but not strong, fusion of sensory data, where
small amounts of visual data might be leaking into the auditory sections,
or small amounts of auditory data was leaking into the visual processing
areas.  But this is just another wild guess.


I don't really follow your logic there.  Are you saying the "imaginary"
thoughts are the ones which don't have of a sensory origin?


Yeah, that's basically the same thing I'm saying anyway.  The tricky part
is when you switch to words like "we can inject" vs, the "the brain is
structured like xyz..." it gets very confusing to understand what the "we"
is you are making reference to and what it means "to inject".  I however
make the same mistake as well and don't always have a good translation to
pure terms of "the brain is structured ...".


Yeah, that's clear.  I've seen others try to justify our ability to talk to
ourselves as a natural evolution of language to allow us to have private
thoughts that other's can't here.  But that doesn't really answer why we
have the ability to have non linguistic thoughts which probably showed up
before language.

Understand the power it gives is fairly easy.  But understanding the
evolutionary path the brain must have undergone to get to what it was
before, and after, is not so easy.


Yeah, I understand the connection to information theory.  I've been looking
at ways to use it to build networks for a long time.  I'm reading "Spikes :
Exploring the Neural Code", by Fred Rieke currently and just hit the
chapter where they jump deep into information theory as a tool for
understanding neural spike trains.


The gray matter which is those millimeters of outer skin is where all the
neocortex neurons are.  The white matter which is most the mass inside is
just backplane.

Most the rest of the brain is not part of the direct pathways from sensors
to effector and not part of our voluntary control system.  The lower brain
seems to be mostly stuff to keep us alive.  The exception is parts of the
midbrain which seem to there to support the operation of the cortex.


Right.  Where I wrote "brain" substitute "neocortex".


Sure it does.  As explained above.


Very true.  There are large sections of cortex which are fed only by a
single modality.  But at some point, the regions all merge.


Right.  That's totally consistent with how I look at it.


But that's not quite how I look at it.

It's just invalid in my view to think that sensory fusion happens after the
visual cortex for example.  The entire visual cortex is doing sensory
fusion.  The eye is not one sensor.  It's millions of them.  And the data
from each of these individual sensors must be fused in the same basic ways
sound and vision data must be fused.  The N layers of visual cortex are
simply fusing individual light sensors into higher level visual concepts.

Likewise, we don't have one sensor signal coming from the ear, we have a
huge bundle of sensory signals coming from each ear which must be fused to
create higher level auditory information.

At some point, these different modalities start to fuse, but it just seems
wrong to think that there was no fusion happening in the visual cortex, and
that some magical "fusion" process then happens when data from the ears
first mixes with high level fused data from the eyes.

Dan and I get into these sort of debates all the time in c.a.p.  He tends
to learn towards the belief that each of the distinct regions of the cortex
that have been mapped out are special designs created by a long process of
evolution to do each special type of data processing task.  So each of the
21 visual areas are each different circuit, doing a different job.  To
duplicate this in our software, we would need to write different software
for processing each type of data.  Fusing left and right eye data would be
a totally different algorithm than fusing ear and eye data.

I on the other hand lean towards far greater reductionism and believe the
entire cortex is basically performing the same algorithm and that each
section, has only had that algorithm tuned to best fit the nature of the
data it is processing.  I believe one algorithm can basically perform all
data fusion.  I believe that it will be found by following ideas just like
you suggested above, with the data compression, and information theory
based ideas.

However, in terms of the "injection point", it seems to me that when I have
memories or thoughts, they seem all directly associated with sensory data.
I have visual memories, or sound memories, or smell memories, etc.  But
yet, as you say, it can't be happening at a very low level, because the
memories are always such a pale echo, of the real thing.  If they happened
at a low level, I would expect them to be more life-like.  So either the
effect is happening higher in the chain, or else, it works as some partial
reactivation staring lower.  This is the stuff that would be so easy to
figure out if we only had high quality brain activity scanners (down the
the neuron level).  How some figures out how to do that without hurting the
brain some day.


Yeah, that seems to be somewhat logical.


I think it's valid to talk about levels.  But it only goes so far since
there seem to be so many feedback loops in the process as well.

But by "entire brain" I was really referring to just the neocortex and
being sloppy in my description, not all areas of the entire brain.

Have you read Jeff Hawkins' book, "On Intelligence"? He too is big on the
belief that the neocortex is the "interesting" part of the brain from an AI
perspective and seems to believe it's basically one algorithm at work.  He
See's it as a data processing problem of extracting invariant
representations - which is basically consistent with various information
theory ways of looking at what the cortex is doing.

The part I think he's missed, and one I stress, is the reinforcement
learning that is needed as well.  Basic data extraction or compression
ideas can lead us to circuits that fuse data and extract the essence of the
information in the data - removing duplicate information that flows in
through different sensory channels (be it from cone to cone in the eye, or
from eye to ear).  This is what would allow us to turn hard to interpret
data like a million pixels of visual data, into signals that tell us
there's a cat in the environment.   But knowing there's a "cat" in the
environment, doesn't answer the question about how we, (or a robot we want
to build) should react to the cat.  Should we chase it as food, or run
away, or just ignore it, or what?.  The basic fusion algorithms are
important in telling us as much as possible about the state of the
environment in a form that's easy to use and as compact as possible (aka
compressed), but you have to add to that reinforcement learning, for the
system to learn how it needs to react to the current state of the
environment to reach its goals (get food, don't let your body be harmed,
reproduce, etc).

--
Curt Welch                                            http://CurtWelch.Com/
curt@kcwc.com                                        http://NewsReader.Com/

Ok, that makes more sense now.

 > The lower, and older brain is mostly not

Hmmm. I'd be very surprised if that's true. It seems you're of the
belief that humans are rational beings - we think before we act -
rather than rationalizing beings, which seems a better description.
Try this - ride a bicycle, then cross your arms and hold the opposite
handlebars. You'll soon learn how effective our conscious is(n't).
Try to make yourself feel grief, or joy, or any other emotion...
rabbits and mice feel most of these things; they're in the mammalian
brain.

My point is that most of our activity and being is arbited by parts
of the brain accessible only indirectly, though we may have awareness
of their functioning.


Yes, but a computer memory can, though structurally amorphous,
contain a story book. The book and the story are not less
structured and real for being contained in an amorphous
mechanism. You might as well say that all of the universe is
amorphous because it's made up of quarks. What you're really
saying is that there's a level of organization that you can't
observe in the material structure with the tools you have -
not that there isn't any organization. So I maintain that
"amorphous" is the wrong term - the functional morphology is
invisible but present in the arrangement of active synapses.


Sorry, the terminology from the book I read on this has faded,
and I can't even remember the title.


Stable *oscillatory* patterns. The time constants in these
oscillatory circuits goes a long way to explain the sensory
process - they form auto-correlators that progressively
firm-up a sensation in the process of representing it as a
particular pattern. It's this idea of temporal correlation
that I think is missing from traditional approaches to robotics
and AI.


I think you're wrong to use the term intelligence only for
the higher functions. A robot that had the same "stay alive"
characteristics would still be an impressive achievement and
be considered intelligent, though perhaps only in the way
that an animal is.


It's not that black and white. I see a dog and perhaps I imagine
it pissing on my leg, but though the idea of the dog is real
(reflects a real present dog), I know that my leg isn't wet. I
don't try to kick the dog because it's pissing on me. The emotion
of revulsion is activated nonetheless, and I probably don't feel
like throwing a stick. IOW the conscious mind knows it has meddled
with its own perceptions, and can still tell which bits are real.
The mammalian brain still responds to having been pissed on, and
generates the appropriate emotion.

If I had lost the distinction of having meddled in reality,
I might just actually kick the dog. Such behaviour is deemed
psychotic. The difference isn't that psychotic individuals
generate more unreality than others, but that they can't tell
they're doing it.

The philosophical question of "why did I imagine that", and
"what is this 'I' that 'decided' to imagine that" is where
the arguments start. My view on that is the same as yours,
I believe. The book is in the computer, and so is the story.
It might look like there can't be a book or a story inside
a bit of silicon, but it's there, it's *all* there.

The idea of the "individual" and all the legal responsibilities
that go with that is a way of identifying a *process* which is
complex beyond prediction, so we hold the *process* itself
responsible for its behaviour. We don't hold the molecules of
a murderer's body responsible - even though they fully embody
the process.


Either that, or your "dog leg" neurons and your "red" neurons
activate to represent a symbol which is defined as a linguistic
element without the need to have a word associated. IOW don't
get hung up on the idea of linguistics needing words. Language
manipulates symbols, whether or not they have words.


I did a review of the state of data compression a year or so
back, and there are some very good ideas in things as common
as ZIP. IMO it would just take an appropriate way of representing
the temporality of a stream of behaviour/sensation and they could
be applied to the creation of muscle memory, so a robot could
learn how to walk - unlike the recorded step-sequences that
allowed Asimo to stand, walk and dance. Clearly they encoded the
required behaviour, and maybe even compressed the encoding, but
dynamic compression and matching of recent event sequences is
what's needed for learning at this level. To my mind, the temporal
content in the data stream is the part we haven't thought about
enough.


Sorry for the typo, I meant to say synaesthesia. But you've
answered my objection by clarifying that your use of "amorphous"
was structural not functional.


Yes, I agree. When I say "sensory fusion", I restrict it to
mean the area where processed data from the different senses
gets fused. That's not to deny that fusion occurs elsewhere.
I was responding to your apparent denial of the functional
morphology, of layers of processing, where in fact you were
just pointing out that there's little structural morphology.

While that's true, I hope I've explained why I think it's
beside the point.


I'm with you on that. It seems unlikely that there's enough
information in the genome to describe the entire schematic
:-).


Which is exactly why I call it a sense of thought. It's
at the level where we're collating the various senses,
but here we're sensing our own thoughts, and the data
has been through a similar amount of pre-processing.


No, sounds like a good one, I'll look it up.


That's just data compression under another name,
as you and I both pointed out.


I don't agree here. We correlate all concurrent events
and the associated emotions & thought patterns in the
process of encoding/compressing. Learning is implicit
in these quality association in the sensory data stream.
If that cat scratched me last time I tried to pat it,
I have a negative association. Because I can do partial
retrieval "that's the same cat", I can recall the
qualitative data that was associated previously.


Can't agree here. Data compression requires memory, and
memories encode learning.

Clifford Heath.

No, I believe we are emotional beings.  Way down at the bottom of the post
I'll explain.


That's a good one!


Your using terms different from how I'm using them.  Let me ignore this for
now because what I have to say below about reinforcement learning touches
on that.


And again, I'll cover emotions below with reinforcement.


You are the one that used it.  I actually am not really familiar with the
term and I just copied your usage as best as I could guess what you were
getting at.


For sure.  Which means it's not invisible at all.  We know the function is
encoded in the synapse and we have no problem seeing the wiring.  We just
don't know what it means.

I'm a strict materialist or physicalist.  I think talk about "function" as
being separate from structure is only a language convention we use.
Function itself can't exist separate from the structure any more than the
human soul can live on after death (which is where I think all this talk
about function not being physical all came from).

We often talk, and think of computer memory devices as having a uniform
physical layout and that the data stored in the memory has some logical or
intangible existence separate from the physical memory.  But in fact, the
data stored in the memory is just as physical as rocks and makes the
physical structure of the memory anything but uniform.  It exists as piles
of elections in typical dynamic computer memory for example and electrons
are very physical.  The fact that we can't see them with our eyes only
helps to further the invalid concepts that data is not always physical.

And likewise, our neocortex stores it's knowledge in it's wiring.  It's a
learning machine which gets wired though experience.  The wiring is
constantly changing, just like our memory is constantly changing.  So even
though I think the neocortex is basically one type of circuit duplicated
over and over, it's training has transformed each circuit into a very
specific circuit that performs one very specific task.


Ok, that's possible.  I've not seen work that describes it that way but I
can relate.


Yeah, that was a big insight I finally grasped about 5 years ago because of
debates here on Usenet in the AI groups.  I had spent many years working
with fairly traditional (non temporal) types of neural networks trained by
reinforcement and though I understand the temporal issue was there, I
always figured we would solve it in our hardware just like we normally
solved those problems. That is, we would create a non-temporal function
mapping function, and then use memory to act as delay devices to create the
temporal aspects.  Technically that's valid, but for practical reasons, I
later discovered it was just the wrong approach.

I worked with mostly binary networks (aka networks with binary signals with
N binary inputs that would produce N binary outputs once every clock
cycle).

Then when I started to grasp the temporal problem, I started to look at the
advantage of working with asynchronous pulse signals (like the brain uses),
and realized that processing nodes that dealt with these signals had a
great advantage.  With the old nodes, I created a spatial function, and
added extra hardware to make those spatial functions perform temporal
pattern matching.  But with pulse signals, you could create gates that
performed temporal functions, and totally ignore the spatial aspect of the
problem.  In fact, there is no spatial aspect of the problem that needs to
be solved - we only are trained to think in those terms so that we can
write down our ideas on a sheet of paper - it was in fact our long history
of using written language that biased our tools and techniques so much
towards the spatial.

For the past many years now, I've only been looking at designs that use
async pulse signals and which mostly, perform all their actions based on
pulse spacing.


Well, if you knew me better, you would know that I'm the one that makes the
argument that rocks are both conscious and intelligent.  So I have no
problem extending the idea of "intelligence" down to levels far below what
must people would. :)  But my use of intelligence above was limited to a
different type of use.  I think most of what people see in human behavior
(and some animals) comes from us being strong reinforcement learning
machines - and the lack of that very specific feature is what prevents most
people from believing a machine could every be the same as a person (that
is, most of the people that have a hard time accepting that idea).


The emotion stuff I'll get to below, but to remove your use of "knows" in
the above, I would simply say that the reason we don't kick the "imaginary"
dog is BECAUSE our leg isn't wet (not because we "know" it's "not real").

Not only is the leg not wet, but a lot of the other current sensory
perceptions don't match with our perception of the dog pissing on us as
well.  And the reason we can tell it's not "real" as you say, is because
all these other things don't match.

I think the memory is in fact very real - just as real as when we see a
real dog piss on our leg.  I think it's represented in the brain in the
exact same way as it's represented when a real dog is pissing on our leg.
There's no "memory that it came from our thoughts" that allows us to tell
the difference.  It's only the fact that it's inconsistent with the the
rest of the data currently in our brain.  So how do we know, when there is
conflicting data, which is "real"?  We can tell because there is far more
"real" data than imaginary data active in a normal brain.  So, I have data
that tells me my leg is dry from feel, I see the ground, and there's no dog
parts to be seen.  I motion detectors didn't tell me something just moved
by my feet.  I'm in a shopping mall, which is a place that I wouldn't have
expected to see a dog.  All this other data, fits, and is consistent with
each other, and is consistent with the idea that there is no dog.  But yet
other data in my brain tells me there is a dog.  So which do I trust as
"real" and which do I trust as the "memory" or "imaginary thought"?  The
one with the most consistent data of course.

And what happens when we sleep and our real sensory flow is cut off and the
only circuits being activated are the ones that are free do so independent
of our thoughts?  We start to think that our dreams are real.  Only when we
wake up, and get a sudden influx of data which is inconsistent with the
"dreams" do the "dreams" stop looking "real".

If we had some memory of the fact that the thoughts were injected (your
idea in my words), then how do you explain the fact that dreams seem so
real to people?  And why do they sudden revert from "real" to "dream" when
we wake up?  Where as my idea, that these memories are in fact exactly as
real as the real thing, but we can spot when they are "invalid" only by
comparing it to what else is going on. (I can explain what I mean by
"comparing it" if you care as well).

Also, my view of dreams and memories gives us more power to understand
mental illnesses like schizophrenia and their associated hallucinations.
If too  much of the brain activates with a "memory" (instead of in direct
response to current sensory data) it becomes impossible for us to tell
which is real, and which is the dream.  The only think that keeps us in
touch with reality, is the fact that most the brain in a normal human, is
being activated in direct response to current sensory inputs. If too much
of the brain reverts to a old states (memories), then we loose track of
what is reality, and what is the dream.

The dreams all become consistent with one another (when we dream a dog
peeing on our leg our leg feels wet) simply because all these sensations
are connected to each other though feedback loops and they have been
trained to form consistent patterns.  So when we have a thought of a dog
peeing, it's biasing our leg to switch to the "I feel the warm wet pee on
my leg", but it's only the current flow of real sensory data that's keeping
that sensation from forming in our brain about our leg.

But if the sensory data starts to loose the battle, and too much of the
mind switches to a dream-like state even when we are awake and functioning,
then we loose touch of reality and start to believe that the these other
false brain states are "real".


And my theory, is that the simple fact that generated to much "unreality"
is WHY they can't tell they did it. :)


Your "book" vs "store" stuff is confusing me a bit.

I don't mix process and function and physical reality.  There is _only_
physical reality.  Process is just a store we create to describe physical
reality.  We can create language to describe how a computer work, and we
can label that language, as being the "process" of the computer.  But the
computer is the computer, is the computer.  It's not the process.  It's the
computer.

And likewise, I am a physical hunk of matter.  That's all I am. I am not a
process.  I am not a mind.  I am a brain.  When I do things, it's my body
doing things.  When I talk about what my mind is doing, or what is "in my
mind", I'm really just talking about what the brain is doing.


I don't like to talk that way.  I hold the body responsible for the crime.
Not the process.  To talk as if the process is responsible for the crime
and not the body is just left over bull shit about the soul being separate
from the body which I don't believe.

If a machine runs out of control and kills someone.  Do we hold the
blueprint for the machine responsible for the action and not the machine
itself?  That would be silly - playing the death on a piece of paper.
That's what I think you are saying when you talk about "us" being the
process.

I agree that nearly everyone on the planet, even all those that are strong
materialist who don't believe there is a soul separate from the body, like
to talk the way you are talking, but it's deceptive in my view.

In one way, I hold that type of talk valid - but confusing.  That is, our
own view of our self exists as kind of a blueprint in our own brain.  It's
like a camera taking a picture of itself and using that picture as it's
only way to understand itself.  Likewise, our view of "self" is limited to
what our brain can represent aboutourself, so it's value in that sense for
me to say that my view of myself is limited to my understanding of myself.

But, like with the camera, we would never say the data encoded on the
picture was the "real" camera.  We would say the physical camera is the
camera.

Likewise, I say that I am a physical body, nothing else, nothing more.


Ok, more semantics.  I like to say that pulses are symbols and that the
brain is a symbol processor just because it's processing pulses.  This gets
people that like to reserve the idea of "symbols" to something closer to
the concepts represented by our natural language words.  These are also the
people that seem to see our language processing skills are something truly
unique to humans and non existent in lower animals.  I don't see it like
that at all.  Words are just temporal patterns to us like everything else
we deal; with.  The brain represents them all, be it a cat, or the word
"cat", in the language of temporal pulse signals.  No where do I believe
there is any significant difference in what the neocortex is doing when
it's processing and producing natural language behavior, or when it's
processing, and producing, all other sensory information.


Though many concepts like this go though my mind as well, finding a working
implementation illudes me.  It's driving me crazy. :)

[snip]


Ok, here's why I answer the stuff I didn't answer above about emotion etc.

What you talk about is in fact reinforcement learning.

You wrote above:


Why is a cat scratch a "negative" association?  That's what you fail to
answer.  How do you formally define what should be a positive association,
and a negative association?  How is this formal definition of "value"
defined in the hardware?  How is it implemented?  The answer is that it's
implemented as a reinforcement learning machine.  That's what I mean by
saying we need to build a reinforcement learning machine.  You must build a
machine that is able to make associations of value.

So, how do we built a robot that would register a cat scratch as a negative
association?  You start by building custom sensors, and hard-wired
processing, which is able to detect pain and pleasure (technically the
wrong words but I'll use them anyway).  We build hardware that knows what
sensory conditions we want to be registered by the machine as "bad" (aka
pain) and what sensory conditions to be registered by the machine as "good"
(aka pleasure or rewards, or reinforcer).  This hardware is called the
critic in reinforcement learning terminology (reinforcement learning is a
specific sub-field of machine learning in AI BTW and I'm not making
reference to the psychology fields of behaviorism - though they are closely
connected).

The learning machine must then receive sensory data, produce outputs, and
receive reward signals from the critic.  To the learning machine, the
critic can be thought of as just another part of the environment, but in a
actual robot, the critic hardware is something we, as the creator, would
design and built.  The critic hardware is what gives the learning machine
it's high level goal, or purpose, in life.  All it's morals, and behaviors,
and drives, are derived from the goals built into the critic.

The only goal of the reinforcement learning machine is to maximize TOTAL
LONG TERM reward. (not to maximize only current reward).  This means it
must constantly estimate potential future rewards, and make constant trade
off decisions about whether a bird in the hand is worth more, or less, than
two in the bush.  That is, given a choice of one behavior with a quick
reward, or another behavior, with a larger, but more risky long term
reward, which behavior is the one expected to produce (on average) the most
total reward per time.  The behavior with the best total reward per time,
is the one the machine should select.

The entire purpose of a reinforcement learning algorithm, is to predict
these values (based on data collected though past experience), and produce
behaviors based on their expected value.

This is NOT the same problem, as the data compression issue or the general
issue of prediction.

A machine can analyze sensory data, and find ways to compress it, and ways
to predict what will happen next in the world (if we stand here we are
likely to be scratched by the cat), but making that prediction, doesn't
tell the machine what to do.  Maybe it "likes" being scratched, so the best
answer is to do nothing and hope the cat does scratch us as predicted.  Or
maybe a cat scratch is bad, so we should take actions to prevent that from
happening.  How does the human brain "known" that a cat scratch is bad?  It
"knows" it, because there are special hard wired circuits in the brain (not
in the neocortex, but in the midbrain) that can sense when harm is done to
the body in various ways, and will in tern, send a "punishment" signal to
the learning brain (the neocortex), so that it can form a negative
association with whatever sensory conditions preceded this punishment (the
vision and sounds and smells of a cat scratching our leg).

Alone with this power, the learning system must use it's power of
prediction, to later predict that just the site of a cat is at least
slightly bad, because once we see a cat, the probability that we will get
scratched just went up, and the prediction system should be able to predict
that - leading to just the site of a "cat" having a low value associated
with.  If ever time we visit a given place, cats show up, then the low
value of the cat, will train the vision of this cat building, so that just
seeing the cat building will produce a punishment (training us not to go
near that building if there are better options to chose from).

All these "values" that the reinforcement learning machine is associating
with all sensory conditions, as well as all behaviors it produces, is the
source of our emotions.  This is what makes us love some things, and hate
or fear others.  If the reinforcement value prediction system predicts high
future rewards for some stimulate (a hot babe), it's what makes us "like"
that sensation, or that object, and it's what makes us increase the odds of
using the behaviors that produce that stimulate condition.  If our
prediction system predicts very low future rewards, that's what makes us
dislike the stimulus and it's what makes us stop producing a behavior that
creates that stimulus condition.

The reason we are emotional machines, is because we are reinforcement
learning machines.  That's where our emotions come from.  If you want to
build an emotional robot, you have to build a robot with a reinforcement
learning engine driving its behavior.

I could talk more, but this post has gone on too long already.  If you want
me to talk more about reinforcement learning, and how it's different from
supervised learning for example, and why I think it's the the only type of
learning that explains human intelligent behavior, (or why it's easy to
know this is the answer, but not know how to code it) I can do more of that
as well.

--
Curt Welch                                            http://CurtWelch.Com/
curt@kcwc.com                                        http://NewsReader.Com/

Ok. Amorphous means simply lacking in structure.
The lack of appearance of physical structures in
the cortex belies the deep function structures, as
I think we've both agreed. I originally thought
you were implying that all of the cortex processes
all of the data, which would have been a silly idea
and demonstrably wrong.


I'm with you on the materialism, but I think you
confound the ideas. A computer memory cell isn't
structurally different for storing a one instead
of a zero, it's functionally different. A RAM
chip is structurally simple - so repetitive - but
the data in it may be functionally rich - e.g. a
story.

One human body isn't structurally different from
another, but they sure are functionally different.


No, but the structure can exist without the function.
The RAM chip has the same structure when it's not
powered. It's not just the arrangement, but the way
the arrangement can change, the way it's *developing*,
that constitutes the process (I'll explain my use of
"process" below).


The opposite approach, as I'd have it. Time and change
is the key, not static modeling. We respond to stimuli
precisely and only because they represent change.


Ok, I can dig that, not sure if I agree though.
The generation of "what-if" scenarios in the brain
makes use of the existing sensory circuitry to
process hypothetical events. When the hypothesized
sensations are injected into the sensory fusion
chain, the change in the outcome is processed
differently than if it had occurred in the absence
of the hypothesis, i.e., in the real world. To
observe this change is the purpose of hypothesizing.

That's what I mean when I refer to tagging - we
can experiment with how we might respond if a
particular event would occur. The re-use of the
sensory chain has side-effects (like changing our
emotional state) even though at a conscious level
we know it wasn't real.


Because of the side-effects of the re-use of
the sensory processing chain, some hypotheses
are unsafe to inject while the motor functions
are active. Nevertheless there's still an
advantage in exploring our likely response to
them; it serves as training for situations
that have not yet occurred. So we can dream of
falling off a cliff, and train a withdrawal
response, without having to actually go near
a cliff. So there's an evolutionary advantage
to dreaming.

A waking hypothesis results in a mental change
that must be separated from the base state in
order to determine its outcome. As a result,
it's somewhat diluted - dreams can be more
intense.


It's more of the structure/function stuff I
wrote about above. The book is "real" while
existing only in a transitory physical state,
only in a temporary arrangement. More below
where I explain "process".


The idea of process is deeper than you
give it credit for. The average duration
for which any given atom is part of a
human's body is around six months. That
is, on average, every atom gets replaced
every six months. So what is the human?
They have a clearly identifiable likeness
and individuality with a much longer time
constant. Clearly the person is a *process*
that exists in an organization of those
atoms, where the process maintains the
organization even as the atoms themselves
change.

You say that "process" is "just" a story
(at least I think you meant to type that),
but that seems like an attempt to deny its
reality and significance. It doesn't consist
of atoms, but it exists through atoms. Its
existence isn't fundamentally different from
the existence of one of those atoms themselves,
which each exist as an arrangement of lower
particles.

Of course the process is a physical phenomenon.
But it's a clearly identifiable phenomenon
having distinct characteristics and duration,
and as such shouldn't necessarily be treated
differently from the physical particles in which
it consists. It doesn't become meta-physical by
being treated as a reality; it's a reality within
a reality.


The body exists only because a process is
maintaining it. They're the same thing.


No, we hold the designer responsible, because we
expect that machines will only be built the bounds
of whose behaviour can be completely predicted by
its designer - that's an expectation we have of
designers.

If we ever change that expectation, and allow
designers to create intelligent robots, we might
blame the designer and wish we hadn't allowed it,
but it'll be the robot that gets destroyed. We'll
hold the robot responsible, of course. But if the
parts are useful, we'll re-use them, they won't
be tarnished with the stigma of what they did when
they participated in the whole thing.

My point is that blame attaches to the thing whose
behaviour cannot have been predicted.


No, it's descriptive. I'm not using the word
metaphysically. You'll probably argue that the
description is not the reality, and I agree,
but I don't think it hurts, so I'm going to
keep doing it. :-).


Whoops, all too self-referential for me. I'm not
going there; it's like an aircraft turning such
sharp corners that it flies up its own tailpipe
and vanishes :-). Not what I intended in my use
of the word "process" at all.


I think we have to invert the priority of time
intervals and datum. The datum is in fact the
change, but the retrieval is based on the rate
of change (or time between events) more than
the amount of change (or the type of event).


I think you're wrong, and it's exactly the same problem.
Long term prediction requires us to test hypotheses,
which we can do using our normal apparatus. The
predictions are based on previous learned responses.
We are sentient precisely because we can do this to a
much higher degree than other animals.

One other comment:

The trouble with your critic is that you assume values.
"Long term reward" measured as what? We have *multiple*
biological drivers that compete to be complied with, and
sometimes they are at odds with each other. These drivers
are the values which our critic uses, though not always
consistently.


You're using the term emotion unconventionally here.
Reptiles are a reinforcement learning engine, but
they do not have emotions, whereas mammals do.
Emotions drive behaviour which has consequences
advantageous for the social or family group, but not
directly for the individual.


It's been good - but it has to be truncated sometime or
it'll never end :-)

Clifford Heath.

This is how I always thought about it until I actually thought about it. :)


You seem to be using "structurally different" in an odd way.  If I'm 6'1"
male and my wife is a 5'7" female you are telling me our bodies are
structurally the same because we are both humans?  We of course share many
structural similarities, but in not structurally the same unless all the
structures are the same.

Not only is the structure from the outside very different, but our brains
are structurally very different as well - which is why she doesn't act like
me, and I don't act like her - we have different programing which is 100%
represented in the structurally differences of our bodies.  That's how I
use the term "structurally different".


Meaning a structure can exist which has no function?  Or just that a
structure can exist which doesn't have a specific function (a car dose not
function as a hammer).


Not at all.  It's _VERY_ different when it's powered.  It has piles of
extra electrons that aren't there for long after the power is removed.
It's the physical structure that determines the memories function.

If you load Microsoft Word into the memory of a computer, this is not just
a "logical" process (how we tend to think of that). The machine has
physical been reconfigured into a word processor by the physical actions of
it's parts.

A computer is just as physical as a clock with gears.  It works for the
same reason a clock with gears works.  The atoms and electrons push each
other around in physical ways constrained by the physical structure of the
machines.

Computers are mechanical devices just like a mechanical clock is
mechanical.

The brain is likewise a mechanical device just like a clock.  It's just got
much smaller parts that operate in more interesting ways that clock gears.
Humans are robots.


Yes, process is nothing more than the documentation of physical motion.


Yeah, but we are built to respond to a lack of change as well. (hit the
button if the light hasn't changed in 10 seconds).  So I think a "change"
centric view might be a bit limiting.  In order for a machine to perform a
task like that, it must have a physical clock which is constantly changing,
so internally, it's all about time based change, but externally, we are not
limited to responding to only sensory changes.


I think you are getting yourself in trouble by not sticking to one
abstraction level when you talk about this.  You say "at a conscious level
we know it wasn't real".  But what does it mean at the hardware level for
the machine to consciously know something?  What physically happens in the
hardware to indicate we know something?

You talk about the brain injecting a hypothetical event into the sensory
circuits.  But what hardware in the brain is generating the event signal to
be injected?  Are you proposing special brain modules which generate the
hypothetical event signals?  How does that module know what type of signal
to inject and when to inject it?

And if we understand the world in terms of our senses, how is it we are not
fooled by the injection of a replacement signal?  Why doesn't the brain
react to the signal exactly as it would if it had come from the eyes?

What general structure are you suggesting, at the hardware level, to
explain these things?

I think the only difference in our views is that I have a pure mechanical
answer to what's going on, and you have a half mechanical and half
subjective answer to how it works (you keep saying we "know" it's not real
but don't explain in mechanical terms how the brain is structured to allow
that to happen).


Hey, that's interesting.  It's the first time I've seen an idea that
actually comes up with what I consider a valid justification for dreaming
while we sleep.  Many people have suggested that sleep is needed to make
the brain work correctly - to reset it self or something like that - and
that in our AI we might have to duplicate the function - I've never
believed that). I believe you are correct and that the dreams we have when
we sleep actually do condition the brain to avoid predicted dangers - or
seek out predicted rewards (we had a dream that "told us" to look under the
rock for the gold).

I think however the main advantage to all this, as you have said, is that
we can do this "dreaming" while we are awake (we can run scenarios and test
options).  The fact that they happen, and can be of use as we are falling
asleep, is just a side effect of the same useful brain feature. (we sleep
simply because we live on a planet that's dark half the time and our body
is optimized for collecting food in daylight so we need to conserve our
energy at night so we have it available in the day when it will do us the
most good for food collecting).


But how is the hardware structured to separate the "base state" from the
injected state?


The "human" is the current structure of our body.

The same problem happens with many effects in nature like waves, or
clouds.

The physical material that makes up a wave changes just like the material
that makes a human changes.


Well, the problem, is that the human you are talking about, is only in your
mind.  The human I talk about is the physical human.  I don't see any
advantage to talking about my body existing in your mind.  I talk about my
body as my body.  Do you see the difference?

I can make a pile of 7 rocks.  Every day, I can replace one of the rocks
with a new rock.  Every week, the pile is totally different from the
previous week - 7 new rocks every week.  But, when I talk to other humans,
I can talk about "my pile of rocks", and we can all know exactly what we
are talking about - it's the stupid pile of rocks that Curt has been
keeping over in the corner for the past 10 years.

I use the same words to describe the rock pile today, that I did 10 years
ago.  It's still, "my rock pile".  But yet, the rock pile itself is not the
same over that entire period.  It's physically very different.  It's made
of very different rocks, in a very different configuration.

So what is hard to understand about this rock pile?  There is the physical
rock pile, and there are the words that we use to describe it, and there
are physical structures in my brain that gives me the ability to talk about
my rock pile, and there's the physical structures in my wife's brain that
lets her talk about my stupid rock pile.

Atoms are not stable either.  They constantly reconfigure themselves from
nanosecond to nanosecond second.  But they maintain enough consistence to
allow us talk about them as being a "thing".

The point I'm making here is that the best way to understand it all, is to
use the physical layer as the lowest level abstraction of what "exists".
The concept of "process" is a creation of our brain, which we use to help
understand the physical world - just like we use language in general as a
tool to understand the physical world.  But the physical world exists
on it's own, independent of the fact that we are trying to talk about, and
define it as a process.


I think so, but you might be using the word story in a different way than I
do.  It can be very hard to find a common ground to talk about concepts
like "process" and "function" and "information", and "knowledge" when we
try to talk about these ideas independent of the observer.  All these
concepts are easy to understand when there's a human in the picture acting
as the observer.  But to talk about brain function, we are forced to remove
the human observer from the picture and suddenly, the meaning of all these
words become problematical.  There were never intended to be used that way.


How can something exist in this universe and not be made of atoms or other
sub atomic particles?


The atoms are all that exists.  If there is something else besides the
atoms, tell me what it is?

This talk you are using about something being the same, but not the same,
at the same time, is just confusion in our language left over from the mind
body confusion - the body soul confusion.  This is where all these ideas of
process came from and where they got messed up.

If you are going to reject the idea of a soul being separate from the body,
you also need to fix all the other words in our language that are based on
the assumption of the human soul being separate from the body.

The words software and hardware for example are just an extension of the
soul body belief.  Software is never "soft".  It's always hardware.  But
since our entire language is based on the idea that it's the soul that is
"seeing" and "understanding" the world instead of the body doing the
"seeing", we developed this large and complex language based on the same
split.

I believe that what you are trying to argue here (without even realizing
why you are doing it), is that the split is real and valid.  And that the
mistake I'm making, is to deny that there is a split.  I say there is only
structure, but you say there is both structure, and process.  And if I
deny process as anything other than the motion of physical material, I'm
leaving "something" important out.  Yes, I'm leaving out the concept of a
soul.

It's the same confusion of mind body.  We don't have a mind and a body.  We
just have a body.  The reason we were taught to use the word mind separate
from the word body is because the language was designed by people that
believed (knew for a fact) that the soul was separate from the body.

But if you believe they were wrong, and that body is just a body which
moves according to the laws of physics, you need to find a new
understanding of what all these other words really mean.


The body is just the body. It's not a body in a reality.  If we choose to
talk about a small part of the universe called one human body, that's
something that is happening in the brain of the person doing the talking.
Concepts are physical. They exist as physical brain structures in the
person that understands, and uses those concepts.  We have this abstract
concept of what a human body is that we make use of when we talk about
human bodies.  But this abstract concept of "human body" is something that
exists in the person doing the talking, not in the human body.  Of course
this is hard to separate when it's a human body talking about a human body.
It would be easier to understand if we had intelligent robots with the same
mental powers so then we could talk about the concept of a human body
existing in the brain of the robot when it was talking, and thinking about,
human bodies.


I thought it was the laws of physics that held the body together?  What is
this magic "glue" called process that holds the body together?


So, when I kill someone, it's God we hold responsible and not me?  Or maybe
Darwin?

You seem to have a very human centric view of reality - that only "humans"
can be held responsible. (this is the typical view most people have and the
one I constantly have to try to beat out of people for them to correctly
understand a true materialistic view of reality).

It again, goes back, to the belief that we are "special" because we have a
soul.  That only a soul can be held responsible for an action, because it's
the soul that is the cause of the action.  Rocks and machines can't be held
responsible because they don't have a soul.  We must always track the cause
back to a soul in order to find out who is "responsible" for the action.
(you can't be a "who" unless you are a soul).

This is the mind-first view of reality that existed in our culture for
thousands of years.  But it's the view that's being demolished, slowly,
piece by piece, by Darwin's Dangerous Idea (I put it in caps because it's
the title of Dennett's book on this topic).  Dennett talks
about Darwin's ideas of evolution being a universal acid which is slowly
eating through all our established beliefs and views - that it has extended
far beyond the reach of biological evolution.  And he's quite right.

Man's entire view of the world was based on an error made long ago - that
the soul is separate from the body, and that only a soul has the power to
act with purpose.  Therefor, only a soul can be held responsible.  And
above the soul of man, was the super mind of God, the soul and the mind
that is the cause of everything.  This is a nice idea, everything seemed to
fit in a nice order, but one which we now understand to be nothing but
hogwash a few no more useful than the flat earth perspective.

This nice little mind first view of reality all started to fall apart when
Darwin figured out that you don't need a soul, to explain the creation, and
the design, of life on earth.  You need nothing more than than simple
physics and the law of motion.  Of course, more than 50% of the people
here in the US still don't understand this, and are still clinging to their
mind-first view of reality, but that's another problem.


Designers are already creating intelligent robots.  :)


Right, of course.  The truth is that there is a causality chain that
creates all physical actions in the universe. It's a causality chain that
acts according to the laws of physics.  In order for us to control the
environment we live in, we learn what the causality chain is, and we
manipulate parts of the chain to get the desired effects we want.  We move
the light switch in order to turn off the light because we understand the
switch is part of the causality chain which is creating the light.

If someone is trying to kill us with a gun, we manipulate different parts
of the physical causality chain to try and prevent this action - we might
take the gun away, or we might try to block the path of the bullet, or we
might try to manipulate the brain of the person to prevent it from causing
the finger to pull the trigger by talking to the person.  In all causes, we
are attempting to use our knowledge about the causality chain to make a
better future for ourselves.

The concept of "holding responsible" is just one way we talk about how we
manipulate a causality chain that has a human brain as a major component
in the chain.


Ah, not really.  We don't blame the weather on the water that falls out of
the sky because we could not predict the behavior of the water molecules do
we?

We assign "blame" to souls.  That's how the word is used in English.  It
comes from a day when people believed that it took a soul to animate
matter.  The idea that matter could animate itself, was mostly unthinkable
in those days - just as the idea that matter could self organize to form
life was unthinkable.

We are slowly extending the use of the word "blame" beyond where it
started, but the progress is slow.  Since souls are nothing but a special
type of machine, where should we draw the line on the correct use of the
word "blame"?  What type of robot would it be valid to "blame" for it's
actions, instead of blaming the designer? :)


Yes, there's no problem in being descriptive as long as you always
understand where the line is.  When we use these common English words to
talk about AI, the line gets very confusing simply because most common
English words were defined back in day when everyone believed in the soul.
Even though some of us have totally rejected that old belief, we still use
the old language with all it's old issues simply because our brain as
been conditioned to think in those terms.


Yeah, that's the problem that happens.  The language we use was built to
talk about something where there was a clean split - the body and soul -
the observer and the observed.  Once you realize the two are one and
the same, things turn back on themselves and vanish up their own tailpipe
as you say.  It gets confusing.


Right, my pulse sorting nodes perform all their actions as a function of
the time space between pulses. Behavior of these nodes are not a function
of a static datum, but on a measure of time.  They act only when they
receive a pulse, but how they react is not a function of the value of the
pulse (a pulse has no value), the action is based on how much time has
passed since the last pulse event happened.  Everything in that type of
network is time based. It's a temporal network.


Yes, that power you speak of is important in humans, I agree with that.
But the question we must find an answer to is what do we need to build in
order to duplicate that power?  How do we build a robot that acts like a
human?

The lowest level hardware is what we have to build, and understand first.
What does that hardware need to be?  We need to reduce all these problems
of making a robot act like humans to the simplest answer we can find.  The
answer I've found, that is the only one I've every found that all other
problems can be reduced to, is a reinforcement learning machine.

Other people working on AI for example have tried to reduce the problem of
AI to a knowledge storage problem.  Others have tried to reduce it to a
logic problem.  What are you suggesting we reduce it to?  A machine which
makes hypotheses?  How does that work exactly?


Some common measure of reward defined in internally in the machine.


That is just the nature of reinforcement learning.  In the end, the machine
must pick one, and only one, behavior at each moment of it's existence.
It can't move the arm up, move it down, and hold it sill, all at the same
time.  The laws of physics dictates that the arm must be in one place at a
time.

When there are conflicting values, the machine must convert those values to
some common currency and compare them.  It must produce an answer as to
which value the machine will select as the "better" value.  This is the
nature of reinforcement learning.  The conversion to a constant currency
can't be avoided.  It happens by default.

In the brain, the neurons end up being rewired as a result of rewards and
punishments.  The conflicting rewards and predictions of rewards acting on
the brain still ends up finding a single answer as to how to rewire
itself. The probability of some past behavior being repeated in the future
has to either go up, go down, or stay the same.  However that probability
changes is the decision the system has made when it weighed the conflicting
values against each other.


Yes, I tend to do that.  But I think it's the correct usage in this
context.


And how do you know that don't have emotions or that they are reinforcement
learning machines?  Is that based on simple empirical evidence or on social
convention of the use of the word "emotions"?


Well, I get into these long debates in comp.ai.philosophy all the time.
It's very useful to get a strong grasp on all these concepts if we are
going to try and build a machine that can act just like a human.  I learn a
little something new every time I argue these points.

If you want to continue to hash out these ideas we could move the thread
there since most of this is not very connected with practical information
on how to program robots even though the entire reason I work on passing
out these ideas is so I can one day build a very interesting robot.

Or, we can drift more towards talking about how one might actually program
any of this in a robot in which case it might not be too off topic for this
group.  I'm game to talk about it at any level.

--
Curt Welch                                            http://CurtWelch.Com/
curt@kcwc.com                                        http://NewsReader.Com/

Very interesting and pertainate post. Let me just take a small portion
for initial reply, and then maybe I will do later posts on more
sections.

I've said it before, that I am greatly influenced by Julian Jaynes
thinking, as recorded in "Origins of Consciousness in the Breakdown of
the BiCameral Mind". I'll be refering to him in my response to this
first section above.

Yes, we can remember the past, and we can call up the past disconnected
from the present senses, but we also have a very unique ability to call
up "memories" of the future. By that I mean we can look at a situation
and play "what it" with it. We can make a premise, okay if I do this,
then this will happen. In my mind "this will happen" can actually be a
little movie of what happens in the future. Then I will change the
premise and wonder, okay if I do this instead, then what will happen,
and another little movie of consequences plays, and so on, till I hit
one I find the results of which to be acceptable.

Where is this stage upon which our little internal plays are produced?
Weirder yet, Who is that character we see playing our part in the play?

Jaynes says this is our internal mind space, and it is big enough to
hold a universe inside, because when we think about the universe,
that's where the thing we're thinking about is, inside our internal
mind space. Also we have a player to put on this stage that is us,
Jaynes calls the "Analog I"

Now Jaynes ideas are very rich and complex, but I'll stop at this one,
because it is an extention of what you've suggested, that humans can
visualize things separate from their current state, and they do this by
reactivating past state.

It's more than that. We can also imagine a play with objects from past
state in a visualized future scenario inside our minds.


Just to recap, it is current and past sensory inputs, but also, a
predict future sensory expectation that drives our behavior as well.

Proof? Easy. If you flinch when you see something come at you, you are
not reacting to past or current sensory input alone (i.e. you feel no
pain yet) but also you are reacting to a future expectation.

Now, what do we do with this conclusion, because many animals flinch.
If you've ever ridden a horse you know how often they make future
predictions on limited input data, jumping from percieved preditors,
whether there or not.

Can horses visualize the future. I'm surprized to hear myself suggest,
Yes, I guess they must. What does that say about their ability to
manipulate mind state?

--
Randy M. Dumse
www.newmicros.com
Caution: Objects in mirror are more confused than they appear.

I'm not familiar with that work but the title does sound familiar.  From
what you write I think I would find it interesting.  But I've already got a
stack of about 4 books on consciousness I've not gotten to. :)


Yes, for sure.


Yes, that sounds consistent with my views.


I don't think we really need that.  It's just automatic.  When you replay a
past experience, it's always from your own perspective.  At best, we might
be replaying a past experience where we witnessed another person, and are
playing it with the idea of it being "us" in place of the other person.


Yes.  But it's also possible to explain how we have this power.

We don't have to assume evolution created this complex "replay" or
"visualization" hardware for us to explain the power.  Instead, we can
explain it in terms of what our normal perception system already has to do.
It has to classify sensory data into invariant representations in order to
drive our behavior.  In other words, when we see a cat, we might see it
from a million different partial angles, but the brain must still recognize
all these different data patterns as being a cat.  It must even classify
sensory data patterns it's never seen before as "cat".  We can explain how
it does this, in terms of simple statistical correlations, and temporal
predictions.

When a simple sold color object (like a circular disk) moves across our
visual field, we can make predictions about what sensory data we expect to
see in the future.  After it's traveled half way across our visual field
(from left to right), we can predict how the visual field is going to look
in the next few frames.  We expect to see a disk, a little further to the
right, and we can predict exactly when, and where, we expect to see it
next.  We can make a temporal prediction about what data we expect to see
next.

Because there are huge amounts of temporal prediction like this possible in
all our sensory data, our pattern matching (aka classification circuits)
end up using this to improve the accuracy of their classifications.  If we
see a dog spinning around, our circuits (because they have seen dogs, and
things spinning many times in the past) can predict that even though we
only see one eye now, that we will soon see the second eye as the head
continues to turn. This gets wired into the decoding circuits, as a bias in
the prediction system.  The circuits that detect motion, are wired, to make
the lower level circuits biased to detect what the system most likely
expects to happen next.  By having these feedback prediction circuits, the
speed and accuracy of the pattern matching is greatly increased.  Instead
of seeing a dog ear, and having to guess if it's a fuzzy rat, or funny
shaped leaf, the brain can instantly classify it as a dog ear simply
because we had already seen the rest of the dog, and our "dog-ear" circuit
was primed to be the first choice answer when something close to a dog ear
showed up in the about the right place in our visual field.  All our
perception circuits get cross wired this way based on how well each one
predicts the other in a temporal manner.

When you take this same hardware and turn off the flow of sensory data and
just let the built in temporal predictive feedback loops activate it based
on what it expects should happen next, it ends up playing back a movie for
you.  It produces a constant running stream of predictions based on what it
thought just happened last.  Each event it "dreams up" keeps triggering the
next most likely event to follow it.

This can be used to explain why we have "what if" hardware.  Our perception
hardware is simply built to work that way.  Put it into some staring
position, and let it run, and it will predict what will happen next.  Feed
it random noise, and it will still extract the best prediction it can from
what it's hearing (the true basis of that movie about hearing ghosts in the
white noise of TVs).

This is why we dream.  Cut off the sensory data, and the what-if perception
hardware just starts making a stream of predictions.  Feed it random noise,
and it still predicts what it thinks is most likely to be "happening" in
that data.

All this perception hardware is tied into our actions as well.  If we
produce an action of reaching out, the prediction hardware will predict
that it should see our arm reach out.  If we reach out and knock something
over, our what-if hardware predicts it should fall over.  So it's not just
watching a move, it's like playing a video game using our own what-if
hardware - which was all created simply for the purpose of pattern
recognition to drive behavior selection, not for the purpose of playing
what-if games.  That power probably showed up later in our evolutionary
history.

One place (other than our dreams) that we see this hardware in action, is
when you listen to a CD and there's a silent pause between songs.  If you
have listened to the same CD many times, right before the next song starts,
you will "hear" the beginning of the song.  This advance prediction of what
is coming next, is driving all our perception.  We just get to hear it at
work in this case because of the silence.


The CD example above is a good one.


But that reaction is better explained by the prediction that conditioning
(aka reinforcement learning) creates than the simple sensory prediction of
the CD example.


I see at least three basic systems at work here.

They include sensory prediction which is an unsupervised learning system
which gathers data simply from repetitive exposure to similar sequences of
sensory events.

Then there is the reinforcement learning to direct the outputs (behaviors)
- which when implemented correctly, ends up back-propagation predictions
about future rewards which ends up creating behaviors that look
"predictive" in nature (duck to prevent being hit).

Horses no doubt have these first two.

The third feature, which is the ability to use the predictive perception
hardware as a what-if tool while at the same time receiving a normal
sensory stream (aka what we might call tuning out our environment and
daydreaming) is something humans seem to have in ways that I'm not aware of
in animals (at least not at the dog or horse level) (though it would be
hard without high quality brain scanners to verify this).

--
Curt Welch                                            http://CurtWelch.Com/
curt@kcwc.com                                        http://NewsReader.Com/

Interesting comment. How do you know the dog doesn't recall a past
memory of being let out?


Not so easy to explain, I think. The following calls for some
conjecture on your part.

Do you think a dog "sees" in a similar manner to how *WE* see, ie by
perceiving some sort of "image" with its brain [however this happens,
which is still a great mystery], or is the dog's perception of its
visual environment totally different from ours? Whatever that might be.

Now, if a dog [and other higher mammals, for that matter] "see" and
perceive in a similar manner to how we do, then it stands to reason
that they also compute a form of internal "mental imagery" similar to
how we do. In which case, when they are dreaming, they probably also
"see" little pictures in their sleeping/dreaming minds, just like we
do.

Some people contend that animals other than humans are fundamentally
different, in their perceptions/etc, but I seriously doubt it. If
you've ever been with a dog on a mountain trail, and seen it bounding
over rocks and logs, and standing atop a peak and craning its neck to
peer down a 2000' rock face, you'll swear the dog perceives a visual
image very similar to ours. How else could it do these things?

It's hard to justify of course.  But it's based on a few things I've
noticed about dogs (I've owned or lived with many over the years but don't
claim to be an expert in any sense).  For one, they seem to learn nothing
quickly.  They are far more creatures of habit than humans are.  If you try
to change their routine, like let them out a new door, instead of the old
door, they keep going back to the old door.  It takes many exposures to a
new routine before you see obvious signs of them learning the new routine.

Second, they show little ability to plan - which I think we do a lot of
with the help of our memory ability.  For example, I used to play with my
dog by throwing a tennis ball in the house which the dog would fetch.  But,
when it rolled under the couch, the dog couldn't fit under the couch to get
it.  But the dog was small enough to run behind the couch and get the ball.
However, trying to teach that dog that trick was close to impossible.   It
would see the ball by looking under the couch, and simply wanted to go
straight to the ball.  If I led the dog around to the side of the couch,
and it saw the ball behind the couch, it would instantly run for it and get
it.

But no matter how many times I did this with the dog, it would never seem
to make the connection that when the ball was behind the couch, it should
give up trying to go straight for it, and instead, run around it.

This I believe shows that the dog can learn to react to what it sees in
front of it, and what happened in the past few seconds, but has a much
harder time learning a longer and more complex sequence of behaviors
(running around).

I suspect humans use their memory, to help solve, and learn the solution,
to these longer term problems.  Like the dog, our ability to directly
learn, has very temporal range.  So, when we first solve, or are shown, the
solution to a long problem, we don't instantly learn to run around the
couch either.  Instead, the next time we see a similar problem, instead of
just automatically knowing we need to run around, a memory of the past
event pops into our head instead.  We have a memory of seeing the ball
behind the couch and then getting it.  This memory then acts to guide our
current behavior to head away from the ball (to get behind the couch).

After multiple times of using our memory to guild us to a solution, the
behavior becomes automatic.  We see the ball roll under the couch and we
don't sit there having memories that then trigger us to act, we just
instantly head off in the direction needed.

So the ability of our mind to call up memories of similar past events seems
to act as a bridge, to allow us to see the path to longer term problems
than the brain can easily learn automatically on its own.  This seems to me
to be our strength in planing and reasoning solutions to new problems,
based on memories of past experience.

The dog's I've owned, never seemed to have this ability and their ability
to solve a problem as simple as running behind a couch to get a ball when
you can't go over it seems beyond them.  You must instead train them to do
it one small step at a time, with many repetitions.

Some animals, such as some birds, I believe have shown unexpected skills at
reasoning out a multiple step solution to a food problem.  I wonder if they
don't in fact have some human like memory skills?


I think they see just like us.  They of course don't think of it as being
an "image" but neither do kids.  We just see things around us and know how
to react to them.


Yes, I believe that's true.  My dog certainly makes woofing like noises and
moves her feet in her sleep at times that makes me thing she is having a
dream very similar to how we do.  We say she must be chasing bunnies when
we see her doing that.


I doubt that as well.


My point is that I can see the the ball roll behind the couch, and have a
mental image pop into my head of me running behind the couch from the last
time I did a task like that.  Once I have that "memory" I then start to act
out the solution which came to me in my "vision".  I suspect dogs don't
have the same ability to have memories pop into their head in the middle of
them running around a forest.  I think there head is consumed with 99.9% of
what they are currently seeing and that's about all it's consumed with.
When they run to the top of a rock and look around, it's not because they
had a thought of rabbits just before that and reacted by running to the
rock to look for rabbits.  Instead, they saw the rock, and reacted to the
rock by running to the top of it because they have learned from experience
that running to a high place is a good thing to do (because in the past it
had led to good things like rabbits). So where rabbits might pop into our
head, and then the sight of the rock, combined with the thought of rabbits,
might make us run to the top of the rock, I suspect the dog didn't have a
thought of rabbits, and just reacted to the rock directly.

When I walk down a trial, I might just as likely be thinking about an AI
problem, or what I might be doing later that day.  Even though I do a lot
of that with language (which we don't expect a dog to do), there is much I
might think about like that is not language related at all.  I might be
getting thirsty and my mind might pop up an image of that water fountain I
saw at the trial head.  This is what I suspect doesn't happen in a dog's
head - at least not anywhere near the extent it can happen in ours.

--
Curt Welch                                            http://CurtWelch.Com/
curt@kcwc.com                                        http://NewsReader.Com/