Uncommon Descent in Numbers - 2nd edition

Three years ago, I put up some pictures showing the number of comments and threads at Uncommon Descent. Now seems to be a good occasion to up-date some of this information.

1. Google Trends

Look for yourself: The phrase Uncommon Descent was most searched for in 2008. After that, everybody had bookmarked the site, so further googling became unnecessary. The same holds true for The Panda's Thumb - both sites are equally popular...

2. Threads per Month

The number of new threads per month peaked in 2011, but is still on a high level - though it seems to be decreasing. What makes all the difference is "News" - a.k.a. Denyse O'Leary - adding her news items. While in 2011/2012, those often were left uncommented, since 2013, they attract the attention of her fellow editors (though I got the impression that some commentators use them for their off-topic-remarks, while others just cannot let the copious factual inaccuracies stand uncommented.)

On Oracles and Weasels

It's once again about Richard Dawkins's weasel algorithm. In his book The Blind Watchmaker, Dawkins gives the following description.

Dawkins describes his algorithm in the following way:

It again begins by choosing a random sequence of 28 letters, just as before:

WDLTMNLT DTJBKWIRZREZLMQCO P

It now 'breeds from' this random phrase. It duplicates it repeatedly, but with a certain chance of random error - 'mutation' - in the copying. The computer examines the mutant nonsense phrases, the 'progeny' of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL. [...] the procedure is repeated.

In my previous posts, I explained how this can be transformed into a program:

1. chose random string
   
2. copy string n times with mutation. NOTE: at this step you don't know which letters are correct in place, so no letter is safe from being mutated!
   
3. chose best fitting string. NOTE: best fitting seems to be generally understood to be the string with the most correct letters, the fitting is expressed by a number between 0 and 28
   
4. Stop, if the number of correct letters is 28, otherwise
   
5. goto 2
   

Some people (including W. Dembski, I think) are baffled by step 3: seemingly, the program has to know the best string and can extract information about it. Therefore, I restate this algorithm slightly:

1. chose random string
   
2. copy string n times with mutation.
   
3. ask oracle which string it likes best
   
4. Stop, if the number of correct letters is 28, otherwise
   
5. goto 2
   

Evaluating a fitness function for an algorithm is like questioning an oracle. Even Robert Marks's and Richard Dembski's web site says so - though they don't think it through.

So, how does the oracle work in Dawkins's case? You present it with a list of strings and it just tells you which string is best ("The computer examines the mutant nonsense phrases, the 'progeny' of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL."). You don't have to know how the oracle deems one string better than the other: it could be that it prefers the string with the most letters correctly in place, or the one which shares the longest substring with its (hidden) target, or perhaps it looks how many letters are right from the begin of the phrase, preferring METHINKS IT IS FROGLIKE XXX to BETHINKS IT IS LIKE A WEASEL, or preferring correct vowels to correct consonants, it could be a combination of these on Fridays, and Saturdays something else....

Could Dembski's algorithm with such an oracle? No. Here is a his algorithm:

1. chose random string
   
2. ask oracle which letters are in place
   
3. if all letters are in place: STOP Otherwise:
   
4. mutate letters which are not in place
   
5. goto 1
   

What Dembski exploits is the knowledge about the inner processes of the oracle: but knowing how it works allows for a deterministic approach - the Hangman game - which terminates in a few steps...

White Screen & Denise O'Leary

My edits at Uncommon Descent obviously aren't welcomed anymore. What a pity: Now there are at two active threads over there discussing Dawkins's and Dembski's weasel algorithms (as described earlier in A Story of Two Weasels, The Latching Weasel, and Dawkins's weasel: it isn't that bad)

Denise O'Leary asked:

Make the code for the program public. Perhaps Richard Dawkins himself or his friends at RichardDawkins.net can finally provide this code (apparently a program written in BASIC).

I tried to enlighten her. After all, the program is now over 20 years old, and may be rotting in a heap of 5 1/4" floppies...

Dawkins describes his algorithm in the following way:

It again begins by choosing a random sequence of 28 letters, just as before:

WDLTMNLT DTJBKWIRZREZLMQCO P

It now 'breeds from' this random phrase. It duplicates it repeatedly, but with a certain chance of random error - 'mutation' - in the copying. The computer examines the mutant nonsense phrases, the 'progeny' of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL. [...] the procedure is repeated.

This is enough to replicate his program:
1. chose random string
2. copy string n times with mutation. NOTE: at this step you don't know which letters are correct in place, so no letter is safe from being mutated!
3. chose best fitting string. NOTE: best fitting seems to be generally understood to be the string with the most correct letters, the fitting is expressed by a number between 0 and 28
4. Stop, if the number of correct letters is 28, otherwise
5. goto 2

The parameters which you can chose is the number of copies n, and the probability that a letter in a string is mutated, p. You may even chose another procedure of mutation - but keep in mind the NOTE of step 2.

It's really basic to realize steps 1 - 5 in the programming language of your choice...

While the edit above made it through Uncommon Descent's gates, I'm not allowed to post the follow-up:

Just to elaborate: The interesting part is what Atom describes as oracle, i.e., the application of the fitness function. In Dawkins description we read

The computer examines the mutant nonsense phrases, the 'progeny' of the original phrase, and chooses the one which, however slightly, most resembles the target phrase

An oracle - a black box - which accomplishes this just hints to one string when presented with a population of strings. No further information has to be exchanged. It is not necessary to know how the oracle defines the best string: It could just hint you to the one with the greatest number of correct letters - or perhaps the one which shares the longest substring with the target phrase.

And that's rather a pity: W. Dembski is a guy who is interested in information, and the amount of information which is transferred from a environment into the algorithm. He should be interested in the flow of this information: How is this information exchanged?
The answer: Via the conversation with the oracle. Could his partition search algorithm work with an oracle a described above? No, as it is not enough to name the best string, the position of the correct letters in the string has to be named, too.
Does Dawkins's algorithm work with such an oracle? Obviously...

"Your comment is awaiting moderation...."

Perhaps I should be grateful that I'm not blocked at Uncommon Descent. Update: Perhaps I should have been grateful that I was not blocked at Uncommon Descent.
But it's rather annoying to wait for a couple of hours to get your comment through moderation while a discussion is ongoing: my edit contributed at 2:52 am today (Aug 26, 2009) has still not appeared over six hours later, though there were fifteen other comments in the meantime. What is so hard in moderating the following?

I took the string
SCITAMROFN*IYRANOITULOVE*SAM
and calculated a next generation using Dawkins's algorithms with populations of 10,50 and 100 - and mutation rates of .04, .05 and .1. The tenth string in the list is the second generation given in the paper of Mark and Dembski. The differences with the first generation are in bold face:

1. SCITAMROFN*IYRANOIEULOVE*SAM
2. SCITAMROFN*IYRANOITULOGE*SAM
3. ECITAMRI*N*IYZANOITULOVE*SAM
4. SCITAMROFN*IYRANOITUL*VE*SAM
5. SCITAMROFN*IYRANOITULOVE*SEM
6. SCITAMOOLNOIYRAMOITULOVE*SEM
7. SCITANROFN*IYYANOITULOVE*SAM
8. SCITIMROFN*JYRANOITULOVE*SAM
9. SCITAMROFN*ICRHNOITSLOWE*SAV
10. OOT*DENGISEDESEHT*ERA*NETSIL

Can anyone spot a difference in the design of the strings? Anyone? KF? Anyone?

I'll stay tuned :-)

Update: Now I've two comments waiting in the queue:

232 - DiEb - 08/26/2009 - 9:39 am Your comment is awaiting moderation.
I try to get involved in the discussion, but my last edit (#213) is now in moderation for nearly seven hours…

Update: After eight hours, the comment got through. But I seem to be blocked from now on....