I was also inspired by one of Dawkins' books suggesting something similar. It was some years ago but I believe Dawkins suggested writing a type of computer script which would mimic natural selection. I wrote a script and was quite surprised at the power it demonstrated.
As I remember the general idea is that you can type in any string of characters you like and then click the 'evolve' button. The computer program then:
1) generates and displays a string of random characters of the same length as the entered string.
2) compares the new string with the displayed string and retains all characters that are the same and in the same position.
3) generates random characters in the string where they did not match in 2 and displays the full string.
4) If the string in 3 matches the string entered by the computer the program stops otherwise it goes to step 2.
The rapidity with which this program converges on the one entered it quite surprising.
This simulation is somewhat different from natural selection especially in that the selection rules are hard coded but I think it does demonstrate the power of random changes to converge when there is strong selection pressure.
A fascinating aid in demonstrating natural selection was built by Darwin's cousin Francis Galton in 1877. A illustration and description can be found here. The amazing thing about this device is that, as described in the article, it has been re-discovered and re-purpose to illustrate the process of Bayesian inference.
I have come to consider this isomorphism between Bayesian inference and natural selection or Darwinian processes in general as a deep insight into the workings of nature. I view natural selection as a method of physically performing Bayesian inference, specifically as a method for inferring means for reproductive success. My paper on this subject may be found here
I have come to consider this isomorphism between Bayesian inference and natural selection or Darwinian processes in general as a deep insight into the workings of nature.
You might like this. ("In fact, I realized, Bayes's rule just is the discrete-time replicator equation, with different hypotheses being so many different replicators, and the fitness function being the conditional likelihood. ")
Hi guys,
I was trying to come up with a helpful analogy to help explain natural selection in simple terms and it occurred to me that the game Hangman might make a useful analogy, albeit an imperfect and simplified one. I'd be interested to hear your thoughts on this and any other useful analogies or strategies for explaining in simple terms how natural selection allows complexity to arise from simplicity and how it is distinct from random chance.
The Hangman analogy I propose would read as follows:
The benefit of this analogy is it's an example of random guesses still having a sense of forward progression (discovered letters are not removed, and gradually build up), and that it refers to a simple game I think most people will be familiar with. You could then go on to explain how a complex adaption takes many more than a dozen steps, that there are many more than 24 possible mutations, and that each guess takes many generations, to give a sense of the timescales involved.
The weaknesses are considerable and include the inability to go backwards (beneficial changes can be lost as well as gained) and the existence of a single specific end goal (the unknown word), rather than this being a continual process without set targets. It also ignores the possibility that a beneficial mutation does not spread throughout the species.
I very much doubt this is an original suggestion, but it seemed a handy simplification of the "password-guessing" analogy I was just reading about in Dawkins' "The Blind Watchmaker". Any comments or alternative methods would be welcome (I'm still not very widely read on the subject of evolution so I'm sure others have put it more clearly than I could).
Thanks for your time.
David