Re: For Sean Pitman: Review of "Meaningful Information"
- From: "Seanpit" <seanpitnospam@xxxxxxxxxxxxxxxxxxxxxxxxxxx>
- Date: 10 Mar 2007 08:50:38 -0800
On Mar 9, 12:17 pm, "Vend" <ven...@xxxxxxxxxxx> wrote:
On 9 Mar, 17:17, "Seanpit" <seanpitnos...@xxxxxxxxxxxxxxxxxxxxxxxxxxx>
wrote:
That is not correct. Forensic science and anthropology look for understood
objects. SETI is looking for a simple fixed beacon operating at constant
frequency and amplitude, with compensation for orbital mechanics.
And how are the objects in question "understood"? How do forensic
scientists and anthropologists "understand" that the objects they find
were likely produced by intelligent human agents verses some other non-
deliberate natural process? The same thing goes for SETI. If SETI
scientists were to find the signal you describe, how would they know
that it was unlikely to be the result of any non-deliberate natural
process?
Anthropology and forensic have a model of the designers they are
looking for. SETI doesn't seem much scientific to me, but in some way
they also have a vague model: they are searching for 'human-like'
aliens.
That's right! They are all looking for something that humans can do
and that other non-intelligent processes of nature cannot do. For
example, humans can make an amorphous-looking rock, but so can non-
deliberate natural processes. Therefore, when an amorphous rock is
found, human-like design is not easily detectable. On the other hand,
humans can make a highly symmetrical polished granite cube with
identical geometric etching carved in opposing faces. This type of
granite cube would be very very difficult for any known non-deliberate
natural process to produce. Therefore, when such a cube is found,
human-like design is clearly evident.
The same thing is true for SETI scientists looking for some "narrow-
band endless sinusoidal signal - a dead simple tone." Like the highly
symmetrical polished granite cube, it isn't very "complex" at all. It
is very simple and highly symmetrical. It is the near perfect
symmetry of the tone and of the granite cube as well as the narrowness
of the band that makes such a pattern so "unnatural" and therefore
such a tip-off of intelligent design. Again, the tip-off here is not
that all simple patterns are the result of intelligent design. That's
simply not true. However, such simple patterns found in certain
media, like radio signals or granite are indeed "artifactual" in
nature because non-deliberate processes don't even come close to
producing such symmetry in these particular materials.
There you have it. Prior experience and knowledge with the material
in question as it relates to non-deliberate natural processes is
needed before intelligent design of any kind (human or otherwise) can
be adequately proposed.
You see, scientists have to have some sort of background with the
material in question as it relates to non-deliberate processes. In
other words, scientists must have some sort of understanding of the
likely potential and limits of non-deliberate processes as they
interact with the material in question. Without this knowledge it
simply isn't enough to "understand" that humans are in fact capable of
producing this or that phenomenon. An understanding of the likely
limitations of non-deliberate natural processes is also required.
What limits?
A random source of letters has the same probability of producing a
Shakespeare play as any other sequence. Humans do not. Thus if you
look at a Shakespeare play you say that it probably human-made.
Humans can produce a random-appearing sequence of letters just like
your "random source". The difference between the two sources is that
the random source cannot produce the informational complexity of a
Shakespearean play this side of a practical eternity of time. The
same thing is true of certain types of patterns, like a series of 1
million A's in a row (given equal possibilities of all 26 letters of
the alphabet) or of having all the red marbles on one side of the box
and all the otherwise identical blue marbles on the other (10,000
marbles total). Such patterns, though quite simple like the simple
radiosignal SETI scientists are trying to find, are quite artifactual
for these particular materials, and therefore indicate deliberate
design.
Now, I know you claim
that any finite pattern can be compressed into a single bit. However,
that's just not true for some sequences since your single bit must
have access to a code that contains a much longer sequence. This
isn't the same thing as compression with use of a formula like Pi or
like "repeat the letter A one million times."
For each finite binary string S you can define (and build) a computer
CS which contains the instruction "output string S".
This computer has the instruction "output string S" encoded with a
single bit, say "0" and other instructions encoded by one or more
bits, with the first bit set to "1".
S has a complexity of one bit when CS is taken as reference computer.
The point is that the database of your reference computer is not
simpler than the sequence in question. Therefore, the sequence is not
truly being "compressed" by the reference computer into one bit.
Compare this to a series of 1 million A's. This sequence can be
significantly compressed without the need for the reference computer
to have a database of a series of 1 million A's. Such true
compression could not be achieved for a Shakespearean play or a
randomly generated series of 1 million characters. See the
difference?
Or, if you like, symmetry can be used as a sort of standard
compressor. The more symmetrical, the more compressible and the less
"random". This method would not be useful for sequences like Pi, but
those sequences that do express greater symmetry most definitely have
less Chaitin complexity or "randomness".
No. Finite strings have an algorithmic complexity that depends on the
reference computer, as I shown before.
Not true. Algorithmic complexity is independent of the reference
computer. If any program could be found to significantly compress a
sequence, without having to first code the entire sequence into its
database, one would have discovered that the sequence has a lower
KCC.
I have, in previous threads, provided you with the reasons, and with the
supporting math, that KCC for a pattern like that ranges from arbitrarily
low to arbitrarily high depending on the choice of reference computer. Have
you forgotten?
I simply don't understand your position here. The above listed
pattern of Rs and Bs is highly compressible using the proper simple
formula. If you can find a more simple expression, then you have
demonstrated that the sequence has less KCC. I simply don't see your
argument at any sequence can be compressed into a single bit as
valid. You appeal to the reference computer requires that the
computer database itself be more complex than the sequence.
Therefore, how have you really "compressed" anything?
How do you measure the complexity of a computer? Can you do it
independantely of another (or the same) reference computer?
Sure. What is the minimum number of bits needed to make the computer
"work" to decode the incoming signal and put out the "proper" output?
Chaitin himself explains this problem in very much the same way.
"Almost everyone has an intuitive notion of what a random number
is. For example, consider these two series of binary digits:
01010101010101010101
01101100110111100010
The first is obviously constructed according to a simple rule; it
consists of the number 01 repeated ten times. If one were asked to
speculate on how the series might continue, one could predict with
considerable confidence that the next two digits would be 0 and 1.
Inspection of the second series of digits yields no such comprehensive
pattern. There is no obvious rule governing the formation of the
number, and there is no rational way to guess the succeeding digits."
Does Chatin conclude that the second string has an higher algorithmic
complexity than the first?
Yes, he does.
Algorithmic Information Theory (i.e., descriptive complexity,
Kolmogorov-Chaitin complexity, stochastic complexity, algorithmic
entropy, or program-size complexity) deals with finite strings as well
as infinite strings. What good would KCC be if it only dealt with
infinite patterns?
It is mostly of theoretical intrest. It deals more with what you can't
do with a computer rather with what you can do.
Algorithmic complexity is not even computable: given a reference
computer, there are some strings whose complexity can't be calculated
by an algorithm, even if you restrict to finte strings.
The final degree of complexity may not be calculable, but the degree
of non-complexity is calculable. And, that is quite useful in many
real-life applications.
Sure, the longer the string, the more reliable the interpretation of
non-randomness or "randomness". However, just because a sequence is
finite does not mean that the interpretation of its KCC is not
useful. It is very useful.
It is not useful for practical purpouses.
You are quite mistaken.
This is the basis of statistics. Las
Vegas is built on this sort of useful application.
Las Vegas built on algorithmic complexity?
Yes, it is.
It seems to me that they are related concepts. That's the point.
How?
The output of a cryptographic strong pseudo-random number generator
seems random to any known statistical test, yet it is generated by
usually very short program.
The usefulness of AC in Las Vegas is not so much in detecting true
randomness as it is in detecting non-randomness.
If a
sequence is algorithmically non-random then it is likely that it was
produced by a statistically non-random process as well. This is how
Las Vegas detectives discover cheaters. Certain patterns just don't
appear "random" and, quite often, they aren't.
Can Las Vegas detectives calculate the algoritmic complexity of the
sequence they observe? What reference computer do they use?
They can indeed detect the lack of algorithmic complexity in the
patterns they observe. That is how they detect deliberate cheating so
effectively.
Sean Pitman
www.DetectingDesign.com
.
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