The weasel program or Dawkins' weasel is a thought experiment and a variety of computer simulations illustrating it. Their aim is to demonstrate that the process that drives evolutionary systems—random variation combined with non-random cumulative selection—is different from pure chance. The thought experiment was formulated by Richard Dawkins, and the first simulation written by him; various other implementations of the program have been written by others.
Origin and structure In chapter 3 of his book The Blind Watchmaker, Dawkins gave the following introduction to the program, referencing the well-known infinite monkey theorem:
I don't know who it was first pointed out that, given enough time, a monkey bashing away at random on a typewriter could produce all the works of Shakespeare. The operative phrase is, of course, given enough time. Let us limit the task facing our monkey somewhat. Suppose that he has to produce, not the complete works of Shakespeare but just the short sentence 'Methinks it is like a weasel', and we shall make it relatively easy by giving him a typewriter with a restricted keyboard, one with just the 26 (capital) letters, and a space bar. How long will he take to write this one little sentence? The scenario is staged to produce a string of gibberish letters, assuming that the selection of each letter in a sequence of 28 characters will be random. The number of possible combinations in this random sequence is 2728, or about 1040, so the probability that the monkey will produce a given sequence is extremely low. Any particular sequence of 28 characters could be selected as a "target" phrase, all equally as improbable as Dawkins's chosen target, "METHINKS IT IS LIKE A WEASEL". A computer program could be written to carry out the actions of Dawkins's hypothetical monkey, continuously generating combinations of 26 letters and spaces at high speed. Even at the rate of millions of combinations per second, it is unlikely, even given the entire lifetime of the universe to run, that the program would ever produce the phrase "METHINKS IT IS LIKE A WEASEL". For a string of 28 characters, with 27 possible characters (A-Z plus space), any randomly generated string has the probability one in 27^28 of being correct; that is approximately one in 10^40. If a program generating 10 million strings per second had been running since the start of the universe (around 14 billion years, or 10^17 seconds), it would have only generated around 10^24 strings by now. Dawkins intends this example to illustrate a common misunderstanding of evolutionary change, i.e. that DNA sequences or organic compounds such as proteins are the result of atoms randomly combining to form more complex structures. In these types of computations, any sequence of amino acids in a protein will be extraordinarily improbable (this is known as Hoyle's fallacy). Rather, evolution proceeds by hill climbing, as in adaptive landscapes. Dawkins then goes on to show that a process of cumulative selection can take far fewer steps to reach any given target. In Dawkins's words:
We again use our computer monkey, but with a crucial difference in its program. It again begins by choosing a random sequence of 28 letters, just as before ... 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. By repeating the procedure, a randomly generated sequence of 28 letters and spaces will be gradually changed each generation. The sequences progress through each generation:
Generation 01: WDLTMNLT DTJBKWIRZREZLMQCO P Generation 02: WDLTMNLT DTJBSWIRZREZLMQCO P Generation 10: MDLDMNLS ITJISWHRZREZ MECS P Generation 20: MELDINLS IT ISWPRKE Z WECSEL Generation 30: METHINGS IT ISWLIKE B WECSEL Generation 40: METHINKS IT IS LIKE I WEASEL Generation 43: METHINKS IT IS LIKE A WEASEL Dawkins continues:
The exact time taken by the computer to reach the target doesn't matter. If you want to know, it completed the whole exercise for me, the first time, while I was out to lunch. It took about half an hour. (Computer enthusiasts may think this unduly slow. The reason is that the program was written in BASIC, a sort of computer baby-talk. When I rewrote it in Pascal, it took 11 seconds.) Computers are a bit faster at this kind of thing than monkeys, but the difference really isn't significant. What matters is the difference between the time taken by cumulative selection, and the time which the same computer, working flat out at the same rate, would take to reach the target phrase if it were forced to use the other procedure of single-step selection: about a million million million million million years. This is more than a million million million times as long as the universe has so far existed.
Implications for biology The program aims to demonstrate that the preservation of small changes in an evolving string of characters (or genes) can produce meaningful combinations in a relatively short time as long as there is some mechanism to select cumulative changes, whether it is a person identifying which traits are desirable (in the case of artificial selection) or a criterion of survival ("fitness") imposed by the environment (in the case of natural selection). Reproducing systems tend to preserve traits across generations, because the offspring inherit a copy of the parent's traits. It is the differences between offspring, the variations in copying, which become the basis for selection, allowing phrases closer to the target to survive, and the remaining variants to "die." Dawkins discusses the issue of the mechanism of selection with respect to his "biomorphs" program:
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