Is universal artificial neural network possible?
sunjig...@yahoo.com.cn
intelligence at present, while each of them only deals with a narrow
scope of applications, although many of them involves considerable
efforts and complicated methods. The current achievements impress us
that true intelligence is far to attain.
It was the borrowed idea from biology decades ago that contributes to
the advent of artificial neural network, which opened the new era
although the the model is much simpler than real brain. But since then
researchers have been concentrating on more and more complex
mathematical methods and rarely pay attention to new developments of
brain research. Nowadays it is reported pictures of dream can be
recorded; a monkey acts on electronic signals passed on to its brain
via an embedded electronic apparatus to its head.
Although I have not reviewed much in how our brain works. I am sure
there are must be limited kinds neurons. A neuron must be capable of
simple processing. Its huge population and connections make it
powerful.
Natural intelligence is based on life substances such as protein. But
lifeless silicon has showed encouraging capacity of intelligence.
Computer calculates much faster than its human inventors; its vast
inventory remembers more accurately and permanently. And recent time
has seen the further development of AI.
Simple structure might be more flexible and efficient, as the
interesting discovery that slow learning MLP is equivalent to Taylor
expansion and function simulation is very efficiently realised using
polynomial[2]. Another example is that simpler polynomial networks are
easier to train[3]. It is easy to understand that using small bricks,
cements, sand and other basic materials, we can build a house into any
shape. The fact is, no matter how complicated a computer application
is, finally it is converted into basic digital operations, such as
Boolean operations, shifting, that are carried out in ALU of CPU. This
is similar to the way of brain.
I believe that digital network composing of neurons with very basic
operations such as Boolean and shift could be trained to compete with
human brain. It is time for AI scientists to cooperate with biology
researchers worldwide.
References
1. How does your brain work?
http://www.sciencemuseum.org.uk/on-line/brain/1.asp
2. Conventional modeling of the multilayer perception using
polynomialbasis functions
http://ieeexplore.ieee.org/Xplore/login.jsp?url=/iel4/72/4678/00182712.pdf?temp=x
3. Polynomial Neural Networks
http://ulcar.uml.edu/~iag/CS/Polynomial-NN.html
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Kenneth P. Turvey
[Snip]
> Although I have not reviewed much in how our brain works. I am sure
> there are must be limited kinds neurons. A neuron must be capable of
> simple processing. Its huge population and connections make it powerful.
>
[Snip]
> I believe that digital network composing of neurons with very basic
> operations such as Boolean and shift could be trained to compete with
> human brain. It is time for AI scientists to cooperate with biology
> researchers worldwide.
[Snip]
This seems relatively simple at first, certainly within our ability to
accomplish in one more generation, but it really isn't. The brain has
evolved over hundreds of millions of years. It has special structures in
it for dealing with different kinds of inputs. We are built with a lot
of the programming already hard wired in the structure of our brains.
This programming took hundreds of millions of years for nature to
develop. Even if we can work out the program 1000 times as fast as
nature, we would all be dead before a human intelligence computer program
existed.
Also, what exactly does human competitive intelligence mean? Turing
provided us with one test, but it isn't the only reasonable one to
choose. It relies only on our ability to communicate and store
knowledge, but a program written to pass the Turing test wouldn't be very
good at spatial relations. It wouldn't be great at strategy or art. To
be honest, a program that passes the Turing test would only have human
competitive intelligence in the most narrow of senses.
I guess what I'm saying is that you have discovered neural networks and
now you want to solve _the AI problem_ with them. They may not be the
best tool, but even if they are it may take a million years to work out
the solution. There isn't necessarily any shortcut.
Of course, we all hope there is a shortcut, and many people are looking
for one now. You're wrong about researchers not looking into these
things. They are; they just aren't making much headway.
--
Kenneth P. Turvey <kt-u...@squeakydolphin.com>
Dmitry A. Kazakov
> On Fri, 25 Apr 2008 05:34:45 +0000, sunjigang1965 wrote:
>
> [Snip]
>> Although I have not reviewed much in how our brain works. I am sure
>> there are must be limited kinds neurons. A neuron must be capable of
>> simple processing. Its huge population and connections make it powerful.
>>
> [Snip]
>> I believe that digital network composing of neurons with very basic
>> operations such as Boolean and shift could be trained to compete with
>> human brain. It is time for AI scientists to cooperate with biology
>> researchers worldwide.
> [Snip]
>
> This seems relatively simple at first, certainly within our ability to
> accomplish in one more generation, but it really isn't. The brain has
> evolved over hundreds of millions of years.
Yes, but it is not the way we are developing and programming our
computation systems. [Let me ignore agile software design and extreme
programming stuff (:-))]
> It has special structures in
> it for dealing with different kinds of inputs. We are built with a lot
> of the programming already hard wired in the structure of our brains.
Even more, it is amazing how these specialized structures keep on being
better than universal artificial ones. In fact, it is only highly
specialized problems on which our universal systems can beat "specialized"
brain.
> This programming took hundreds of millions of years for nature to
> develop. Even if we can work out the program 1000 times as fast as
> nature, we would all be dead before a human intelligence computer program
> existed.
That would probably result in nothing. The set of programs is too large to
enumerate it by brute force. Further, there is no any workable criterion of
intelligence, obviously the Turing test is unusable for that purpose. Maybe
the memory chips you have bought already contain an intelligent program,
but how could you know it? So intelligence cannot even be stated as an
optimization problem.
[...]
> Of course, we all hope there is a shortcut, and many people are looking
> for one now. You're wrong about researchers not looking into these
> things. They are; they just aren't making much headway.
Yes. I would also add that imitation of biological systems never was any
good idea. The evolutionary requirements put on species are way different
from what an artificial system serving our purposes would have. Certainly
we would not like an intelligent system that sleeps eight hours a day and
sips beer the rest of watching sports on TV. There is a general problem
with shortcuts. When something worked, but we didn't know why and how, it
could be worth of nothing. Mankind has been producing such intelligent
systems for centuries...
--
Regards,
Dmitry A. Kazakov
http://www.dmitry-kazakov.de
Kenneth P. Turvey
> That would probably result in nothing. The set of programs is too large
> to enumerate it by brute force. Further, there is no any workable
> criterion of intelligence, obviously the Turing test is unusable for
> that purpose. Maybe the memory chips you have bought already contain an
> intelligent program, but how could you know it? So intelligence cannot
> even be stated as an optimization problem.
What I was trying to get at here was more a simple description of the
problem complexity. We only know of one system with human competitive
intelligence, that is humans themselves. We also have a good idea how
long it took to come up with a program for these systems. Right now we
have no evidence to indicate that we could do much better in developing
the software for a human competitive system. We could argue that
evolution is slow, but that doesn't really put an upper bound on the
complexity of the problem of developing such a program.
I have to disagree with your assessment of whether it is an optimization
problem or not. We may not have a well defined fitness function, but we
certainly use one in practice. We could spend some time interacting with
a given system and rate it based on what we perceive its intelligence to
be, where 100 is roughly average human intelligence. The fact that we
could participate in this exercise indicates that we do have something we
are trying to optimize.
Now, that said, I would be more comfortable if we broke into a number of
dimensions and recognize that we are really trying to optimize many
different things, but this is still an optimization problem.
--
Kenneth P. Turvey <kt-u...@squeakydolphin.com>
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Dmitry A. Kazakov
> On Sun, 27 Apr 2008 08:23:48 +0000, Dmitry A. Kazakov wrote:
>
>> That would probably result in nothing. The set of programs is too large
>> to enumerate it by brute force. Further, there is no any workable
>> criterion of intelligence, obviously the Turing test is unusable for
>> that purpose. Maybe the memory chips you have bought already contain an
>> intelligent program, but how could you know it? So intelligence cannot
>> even be stated as an optimization problem.
>
> What I was trying to get at here was more a simple description of the
> problem complexity. We only know of one system with human competitive
> intelligence, that is humans themselves.
Actually, I would challenge that too, for the reason that we don't know
what is essential for being either human or intelligent. Using one
ill-defined thing in order to clarify another, brings nothing.
> We also have a good idea how
> long it took to come up with a program for these systems.
But they weren't programmed. Programming is an engineering activity, which
evolution (at least in theory) is not. Even if we considered the hypothesis
of creative design, the comparison would still be invalid because
1. the programmer teams are different
2. we have no idea how we, intelligent things, program other intelligent
things. We just don't, which is incidentally the whole problem...
3. even less we know about how our alleged masters did.
> Right now we
> have no evidence to indicate that we could do much better in developing
> the software for a human competitive system. We could argue that
> evolution is slow, but that doesn't really put an upper bound on the
> complexity of the problem of developing such a program.
It certainly puts some time constraint, statistically. However that is
probably irrelevant as the event already happened - we call themselves
intelligent. A real constraint for Turing-complete systems could exist if
our brain used some incomputable elements.
> I have to disagree with your assessment of whether it is an optimization
> problem or not. We may not have a well defined fitness function, but we
> certainly use one in practice. We could spend some time interacting with
> a given system and rate it based on what we perceive its intelligence to
> be, where 100 is roughly average human intelligence. The fact that we
> could participate in this exercise indicates that we do have something we
> are trying to optimize.
OK, that would be a Turing test. I have a problem with it, because it does
not confirms anything as intelligent. It rather does that the tester is not
enough intelligent to denounce the respondent. I.e. if this is a fitness
function then for another problem.
> Now, that said, I would be more comfortable if we broke into a number of
> dimensions and recognize that we are really trying to optimize many
> different things, but this is still an optimization problem.
Maybe we could state it as an optimization problem if we knew more about
what intelligence is, but we didn't so far. We also know nothing about the
complexity of the problem if stated in this form. Evolution is solving a
completely different problem and the best solutions found (bacteria,
insects etc) aren't any intelligent.
--
Regards,
Dmitry A. Kazakov
http://www.dmitry-kazakov.de
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Kenneth P. Turvey
>> What I was trying to get at here was more a simple description of the
>> problem complexity. We only know of one system with human competitive
>> intelligence, that is humans themselves.
>
> Actually, I would challenge that too, for the reason that we don't know
> what is essential for being either human or intelligent. Using one
> ill-defined thing in order to clarify another, brings nothing.
In this case it actually does bring something. We agree that humans are
intelligent beasts. That means that such a thing can be created.
Second, since we know how long it has taken humans to evolve, we can
develop at least a general idea of the likely complexity of the problem.
>> We also have a good idea how
>> long it took to come up with a program for these systems.
>
> But they weren't programmed. Programming is an engineering activity,
> which evolution (at least in theory) is not. Even if we considered the
> hypothesis of creative design, the comparison would still be invalid
> because
I'm not even considering creative design (no evidence for it). The
comparison is valid since using evolution to solve the problem is
certainly one way of doing it.
> 1. the programmer teams are different
>
> 2. we have no idea how we, intelligent things, program other intelligent
> things. We just don't, which is incidentally the whole problem...
>
> 3. even less we know about how our alleged masters did.
All three of these seem to assume intelligent design of some sort. We
got from not having a program to having one through a series of finite
improvements. This sounds very much like programming to me. It doesn't
require any goal oriented entities.
>> Right now we
>> have no evidence to indicate that we could do much better in developing
>> the software for a human competitive system. We could argue that
>> evolution is slow, but that doesn't really put an upper bound on the
>> complexity of the problem of developing such a program.
>
> It certainly puts some time constraint, statistically. However that is
> probably irrelevant as the event already happened - we call themselves
> intelligent. A real constraint for Turing-complete systems could exist
> if our brain used some incomputable elements.
Ok, to me this is silly. Just my opinion. If it was not computable,
then our brain clearly couldn't compute it.
> OK, that would be a Turing test. I have a problem with it, because it
> does not confirms anything as intelligent. It rather does that the
> tester is not enough intelligent to denounce the respondent. I.e. if
> this is a fitness function then for another problem.
OK, you and I simply view the world differently. I'm going to have to
side with Turing on this. If you can't tell if it apart from a human
then it must be as smart as a human at least in the dimensions of
interaction. I can't tell exactly what's going on in your mind either,
but I assume you are intelligent since your interaction with me leads me
to that conclusion.
>
>> Now, that said, I would be more comfortable if we broke into a number
>> of dimensions and recognize that we are really trying to optimize many
>> different things, but this is still an optimization problem.
>
> Maybe we could state it as an optimization problem if we knew more about
> what intelligence is, but we didn't so far. We also know nothing about
> the complexity of the problem if stated in this form. Evolution is
> solving a completely different problem and the best solutions found
> (bacteria, insects etc) aren't any intelligent.
We can state it as an optimization problem already. We do it all the
time. That's what standardized testing is all about. We do it in many
other ways too. When you got your drivers license you passed a small
portion of a human intelligence test. We could very easily put together
100 of these and come up with a metric for what it means to have roughly
human level intelligence. Not only would it not be hard, most of the
work would already have been done.
We may not have a good scientific definition of what intelligence is, but
we have a very good working definition of what it is.
--
Kenneth P. Turvey <kt-u...@squeakydolphin.com>
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Jonathan
wrote:
>
One thing we have to consider is that the Human brain (any brain), and
the "intelligence" it conveys does not exist in isolation. Rather, it
is an integral part of the whole body and has evolved to work with
that body.
If we transplant a human brain into a dog (don't try this at home
kids) then we wouldn't expect that dog to be able to talk or even to
walk. The "hardware" just isn't made to fit the "software". In fact,
the result probably wouldn't appear to be very intelligent at all,
just a blubbering wreck.
Side note: This example is actually not extreme enough because there
are likely to be enough similarities between human and dog physiology
that the brain could actually adapt and show some signs of intelligent
behaviour. So, if it helps the argument, consider a human brain
working a house fly where the eyes are constructed in an entirely
different way to mammals, there are too many legs plus there's those
flappy wing things on the back.
So, although our brains have a "general intelligence" aspect to them,
that can only be measured or observed within the context of system for
feeding it with sensory information (text in the case of the classic
Turing text, sight, sound, smell, touch, etc. for humans) and a means
to express some behaviour (text on a vdu or speech and muscle
activity).
In the absense of a true, measurable definition of "intelligence",
Turing tests are about the best we have - using one intelligent being
to "vote" on the level of intelligence of another being. Is an
earthworm intelligent? What about a frog? I sometimes even wonder
about some of my neighbours!
So we could devise 100 (1000?) Turing tests to cover (all) aspects of
percieved intelligence as a means for measurement but they have to be
tailored to the being as a whole.
Passing a driving test in a standard car might be a good test for a
humanoid robot. If it could climb in and out of a car, understand the
examiner, communicate back, control the car, perform the desired
manoeuvres and take into account everything else going on in the
environment then it's certainly showing a lot of intelligent
behaviour. In fact, that one test probably involves many other smaller
tests.
On the other hand, maybe it could just be clever programming for that
specific task rather than general intelligence. Could it also make a
good cup of tea for instance? More to the point, if it can't, is that
because of a lack of intelligence or a lack of the right hardware to
pick up the delicate teabags and pour from the kettle? My dog can't
make tea but I'd definitely call it intelligent.
So the tests have to be applicable to the capabilities of the being
under test.
Could we develop a universal intelligence "module" (neural network or
otherwise)? I don't see why not but if it's going to be "plugged in"
to an artifical being (robot or "deep thought" type computer) and be
immediately useful then it will have to be pre-programmed (as a
starting point) from an identical module that has already been trained
on the same kind of hardware and for the same purpose. In this sense,
"training" could mean evolution, incremental improvement, optimisation
of fitness for purpose or any other applicable technique.
And there's the rub. How could the training occur and how long would
it take?
Dmitry A. Kazakov
> On Tue, 29 Apr 2008 10:40:53 +0000, Dmitry A. Kazakov wrote:
>
> Second, since we know how long it has taken humans to evolve, we can
> develop at least a general idea of the likely complexity of the problem.
No, because the medium is different. For example, it is known,
statistically, how long it would take for silicon atoms to form a
transistor through thermodynamic movement of particles. That does not
estimate the complexity of producing Pentium IV chips.
> The
> comparison is valid since using evolution to solve the problem is
> certainly one way of doing it.
How so? Evolution is a statistical process. We have just one sample of
evolutionary process leading to us. Statistically, this shows perfectly
nothing.
>> It certainly puts some time constraint, statistically. However that is
>> probably irrelevant as the event already happened - we call themselves
>> intelligent. A real constraint for Turing-complete systems could exist
>> if our brain used some incomputable elements.
>
> Ok, to me this is silly. Just my opinion. If it was not computable,
> then our brain clearly couldn't compute it.
This is a different thing. Real-time clock is incomputable, yet any modern
CPU has it. The very idea of an incomputable element is to compute
something, which cannot be computed otherwise.
[Relevant here is only whether incomputable elements (if any) could be
built using available technology.]
>> Maybe we could state it as an optimization problem if we knew more about
>> what intelligence is, but we didn't so far. We also know nothing about
>> the complexity of the problem if stated in this form. Evolution is
>> solving a completely different problem and the best solutions found
>> (bacteria, insects etc) aren't any intelligent.
>
> We can state it as an optimization problem already. We do it all the
> time. That's what standardized testing is all about. We do it in many
> other ways too. When you got your drivers license you passed a small
> portion of a human intelligence test. We could very easily put together
> 100 of these and come up with a metric for what it means to have roughly
> human level intelligence. Not only would it not be hard, most of the
> work would already have been done.
That is not enough. You have to show existence of an optimum, or at least a
countable number of local optimums.
> We may not have a good scientific definition of what intelligence is, but
> we have a very good working definition of what it is.
It is possible that a scientific definition does work (impracticable), but
an unscientific one certainly doesn't.
--
Regards,
Dmitry A. Kazakov
http://www.dmitry-kazakov.de
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Stephen Wolstenholme
<mai...@dmitry-kazakov.de> wrote:
>On Tue, 06 May 2008 03:52:01 GMT, Kenneth P. Turvey wrote:
>
>> On Tue, 29 Apr 2008 10:40:53 +0000, Dmitry A. Kazakov wrote:
>>
>> Second, since we know how long it has taken humans to evolve, we can
>> develop at least a general idea of the likely complexity of the problem.
>
>No, because the medium is different. For example, it is known,
>statistically, how long it would take for silicon atoms to form a
>transistor through thermodynamic movement of particles. That does not
>estimate the complexity of producing Pentium IV chips.
That's interesting. No reproduction or selection pressure so we don't
see "natural" transistors.
Steve
--
EasyNN-plus. Build Neural Networks. http://www.easynn.com
SwingNN. Forecast the Future. http://www.swingnn.com
Neural Planner Software Ltd http://www.npsl1.com
Kenneth P. Turvey
> On Tue, 06 May 2008 03:52:01 GMT, Kenneth P. Turvey wrote:
>
>> On Tue, 29 Apr 2008 10:40:53 +0000, Dmitry A. Kazakov wrote:
>>
>> Second, since we know how long it has taken humans to evolve, we can
>> develop at least a general idea of the likely complexity of the
>> problem.
>
> No, because the medium is different. For example, it is known,
> statistically, how long it would take for silicon atoms to form a
> transistor through thermodynamic movement of particles. That does not
> estimate the complexity of producing Pentium IV chips.
It certainly puts an upper limit on it, which is what I was saying.
Unless you have evidence that a more efficient method will work for
making Pentium IV chips you have no reason to believe that thermodynamic
movement isn't the best you can do, additionally.
>
>> The
>> comparison is valid since using evolution to solve the problem is
>> certainly one way of doing it.
>
> How so? Evolution is a statistical process. We have just one sample of
> evolutionary process leading to us. Statistically, this shows perfectly
> nothing.
So you can learn nothing from statistics?
>>> It certainly puts some time constraint, statistically. However that is
>>> probably irrelevant as the event already happened - we call themselves
>>> intelligent. A real constraint for Turing-complete systems could exist
>>> if our brain used some incomputable elements.
>>
>> Ok, to me this is silly. Just my opinion. If it was not computable,
>> then our brain clearly couldn't compute it.
>
> This is a different thing. Real-time clock is incomputable, yet any
> modern CPU has it. The very idea of an incomputable element is to
> compute something, which cannot be computed otherwise.
This just doesn't follow your assertion above.
>
> [Relevant here is only whether incomputable elements (if any) could be
> built using available technology.]
>
>>> Maybe we could state it as an optimization problem if we knew more
>>> about what intelligence is, but we didn't so far. We also know nothing
>>> about the complexity of the problem if stated in this form. Evolution
>>> is solving a completely different problem and the best solutions found
>>> (bacteria, insects etc) aren't any intelligent.
>>
>> We can state it as an optimization problem already. We do it all the
>> time. That's what standardized testing is all about. We do it in many
>> other ways too. When you got your drivers license you passed a small
>> portion of a human intelligence test. We could very easily put
>> together 100 of these and come up with a metric for what it means to
>> have roughly human level intelligence. Not only would it not be hard,
>> most of the work would already have been done.
>
> That is not enough. You have to show existence of an optimum, or at
> least a countable number of local optimums.
We know that human level intelligence exists. Since we aren't looking
for an optimum intelligence, but only a sufficient intelligence, your
argument doesn't make much sense.
We can still view it as an optimization problem that can be stopped
early, once a human level intelligence is found.
>> We may not have a good scientific definition of what intelligence is,
>> but we have a very good working definition of what it is.
>
> It is possible that a scientific definition does work (impracticable),
> but an unscientific one certainly doesn't.
So the fact that I can give you a good metric isn't sufficient? You must
also have a metric that is objective and contains no noise? That would
be quite a surprise to many in the evolutionary computation field.
--
Kenneth P. Turvey <kt-u...@squeakydolphin.com>
[ comp.ai is moderated ... your article may take a while to appear. ]
Dmitry A. Kazakov
> On Thu, 08 May 2008 10:10:57 +0000, Dmitry A. Kazakov wrote:
>
>> On Tue, 06 May 2008 03:52:01 GMT, Kenneth P. Turvey wrote:
>>
>>> On Tue, 29 Apr 2008 10:40:53 +0000, Dmitry A. Kazakov wrote:
>>>
>>> Second, since we know how long it has taken humans to evolve, we can
>>> develop at least a general idea of the likely complexity of the
>>> problem.
>>
>> No, because the medium is different. For example, it is known,
>> statistically, how long it would take for silicon atoms to form a
>> transistor through thermodynamic movement of particles. That does not
>> estimate the complexity of producing Pentium IV chips.
>
> It certainly puts an upper limit on it, which is what I was saying.
1. To know an upper limit of complexity is useless, unless it is not proved
the least upper bound. For Pentium it is not, what makes you think it is
for "intelligent"?
2. It is incomparable anyway, because, as I said before, evolution is not
engineering. "Complexity of evolution" has no meaning for engineering and
reverse.
>> How so? Evolution is a statistical process. We have just one sample of
>> evolutionary process leading to us. Statistically, this shows perfectly
>> nothing.
>
> So you can learn nothing from statistics?
Nothing from *this* statistics.
>>>> It certainly puts some time constraint, statistically. However that is
>>>> probably irrelevant as the event already happened - we call themselves
>>>> intelligent. A real constraint for Turing-complete systems could exist
>>>> if our brain used some incomputable elements.
>>>
>>> Ok, to me this is silly. Just my opinion. If it was not computable,
>>> then our brain clearly couldn't compute it.
>>
>> This is a different thing. Real-time clock is incomputable, yet any
>> modern CPU has it. The very idea of an incomputable element is to
>> compute something, which cannot be computed otherwise.
>
> This just doesn't follow your assertion above.
The brain cannot compute 10341st root of pi, but it certainly can read a
result of such computing. When comparing computational power required for
intelligence we should clearly distinguish the system itself and the tools
it uses, even if these tools are products of its functioning. You certainly
would not allow driving cars in athletics...
>>>> Maybe we could state it as an optimization problem if we knew more
>>>> about what intelligence is, but we didn't so far. We also know nothing
>>>> about the complexity of the problem if stated in this form. Evolution
>>>> is solving a completely different problem and the best solutions found
>>>> (bacteria, insects etc) aren't any intelligent.
>>>
>>> We can state it as an optimization problem already. We do it all the
>>> time. That's what standardized testing is all about. We do it in many
>>> other ways too. When you got your drivers license you passed a small
>>> portion of a human intelligence test. We could very easily put
>>> together 100 of these and come up with a metric for what it means to
>>> have roughly human level intelligence. Not only would it not be hard,
>>> most of the work would already have been done.
>>
>> That is not enough. You have to show existence of an optimum, or at
>> least a countable number of local optimums.
>
> We know that human level intelligence exists.
What is the set, where the solution is looked for?
>>> We may not have a good scientific definition of what intelligence is,
>>> but we have a very good working definition of what it is.
>>
>> It is possible that a scientific definition does work (impracticable),
>> but an unscientific one certainly doesn't.
>
> So the fact that I can give you a good metric isn't sufficient?
In which sense is it good? Let a value is 345. What does this mean? It
isn't even well-ordered. Apart from that 95% of people would claim their
dogs more intelligent than the boss.
> You must
> also have a metric that is objective and contains no noise? That would
> be quite a surprise to many in the evolutionary computation field.
No, I would like to know the properties of the metric and of the noise.
Whether something like the law of large numbers is true, etc.
--
Regards,
Dmitry A. Kazakov
http://www.dmitry-kazakov.de
[ comp.ai is moderated ... your article may take a while to appear. ]
Kenneth P. Turvey
> On Thu, 08 May 2008 10:10:57 +0000, Dmitry A. Kazakov wrote:
>
>> On Tue, 06 May 2008 03:52:01 GMT, Kenneth P. Turvey wrote:
>>
>>> On Tue, 29 Apr 2008 10:40:53 +0000, Dmitry A. Kazakov wrote:
>>>
[Snip]
>>>> It certainly puts some time constraint, statistically. However that
>>>> is probably irrelevant as the event already happened - we call
>>>> themselves intelligent. A real constraint for Turing-complete systems
>>>> could exist if our brain used some incomputable elements.
>>>
>>> Ok, to me this is silly. Just my opinion. If it was not computable,
>>> then our brain clearly couldn't compute it.
>>
>> This is a different thing. Real-time clock is incomputable, yet any
>> modern CPU has it. The very idea of an incomputable element is to
>> compute something, which cannot be computed otherwise.
>
> This just doesn't follow your assertion above.
[Snip]
I should probably have been more clear. You mention that these
incomputable elements might be a real constraint for our hypothetical
Turing-complete system. To me this implies that these elements reduce
the complexity of the problem significantly bringing it within our
grasp. If this is the case you are really talking about Oracles, not
sources of random inputs or time.
Dmitry A. Kazakov
> I should probably have been more clear. You mention that these
> incomputable elements might be a real constraint for our hypothetical
> Turing-complete system. To me this implies that these elements reduce
> the complexity of the problem significantly bringing it within our
> grasp.
Yes
> If this is the case you are really talking about Oracles, not
> sources of random inputs or time.
But these are no less oracles, anything is if cannot be looked into. I
understand the motivation behind your question. Let we have a DFA wiring
some incomputable elements. The thing turns to be intelligent. Where is the
intelligence hidden? In the wiring or in the "oracles." (What makes a man,
the body or the soul? (:-)) I don't know it.
--
Regards,
Dmitry A. Kazakov
http://www.dmitry-kazakov.de
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Now I wonder if ANN is simulating biological neurons as stated. Since
generally different kind of substances has different kinds of nature;
so features of different system cannot be simulated using same
mechanism.