Joined: June 2008
Thinking about the problem of evolving a code, I just wanted to bounce some ideas off of anyone that wants to answer...
Here is a genome design:
6*26 bits of data to build a phenotype, followed by
64*8 bits of coding table
The coding table works like this. Each entry contains an 8 bit string. Each 8 bit string mapt to a list of affinities to a subset of 32 characters:
127 -> 20% A, 40% F, 40% J
This table of affinities would be salted with entries that guarantee A-Z have some entry with high affinity.
The GA works like any binary coded GA. To create a phenotype, run the data section of the genome through the code table 6 bits at a time. The 6 bits are like the three codons in DNA, mRNA, and tRNA. Taken as an index, they give an 8 bit value. The 8 bit value gives a set of affinities, and you spin the roulette wheel to see which letter you get. That letter is the phenotypic expression of the 6 bits you started with. Continue to loop until you've finished the data section of the genome.
To score a phenotype, compare with the string A .. Z and take the sum of the squared error at each position (ex target D, actual A, error is 3).
I think that if it works, you'll eventually get a population with the code table filled with at least one copy of each high affinity 8 bit string.
Comments? Is choosing 32 useful entries out of 256 too easy or too hard?
I’m referring to evolution, not changes in allele frequencies. - Cornelius Hunter
I’m not an evolutionist, I’m a change in allele frequentist! - Nakashima