Richard Feynman's Affair With Simulated Evolution
Interesting finding this one. Surely I am not joking, but I should state it is not a profound and complete involvement of Feynman's part -- at least I see through this way and I would not get surprised if I am totally wrong about that. However, as the paper author stated in another article:
The last project that I worked on with Richard was in simulated evolution. I had written a program that simulated the evolution of populations of sexually reproducing creatures over hundreds of thousands of generations. The results were surprising in that the fitness of the population made progress in sudden leaps rather than by the expected steady improvement. The fossil record shows some evidence that real biological evolution might also exhibit such "punctuated equilibrium," so Richard and I decided to look more closely at why it happened. He was feeling ill by that time, so I went out and spent the week with him in Pasadena, and we worked out a model of evolution of finite populations based on the Fokker Planck equations. When I got back to Boston I went to the library and discovered a book by Kimura on the subject, and much to my disappointment, all of our "discoveries" were covered in the first few pages. When I called back and told Richard what I had found, he was elated. "Hey, we got it right!" he said. "Not bad for amateurs."
It would be interesting showing before Feynman's eyes what have been done in the evolutionary computation field since then. His mind is the kind of those the field needs.
Amazing reading for a Saturday afternoon. :)
Labels: Artificial Evolution, Evolution, Evolutionary Algorithm, Evolutionary Computation, Evolutionary Optimization, Nobel Prize, Physics, Richard Feynman, Simulated Evolution, W. Daniel Hillis
2 Comments:
Thanks for this link, very interesting reading indeed!
ello, I came across your posting today and was wonderign if you could give me advice. To be direct, I hate my job and would like to explore an occupation within the bioinformatics field. Before dropping a ton of $$ on school, are there any good bioinformatics resources you could recommend?
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