From b721fd62b1f55cfe4dfa10f8155020c2fc9faff2 Mon Sep 17 00:00:00 2001 From: nathan Date: Sun, 27 Mar 2016 19:45:15 -0400 Subject: [PATCH 1/2] Finished Toolbox --- .evolve_text.py.swp | Bin 0 -> 4096 bytes evolve_text.py | 50 +++++++++++++++++++++++++++++++++++++++++--- 2 files changed, 47 insertions(+), 3 deletions(-) create mode 100644 .evolve_text.py.swp diff --git a/.evolve_text.py.swp b/.evolve_text.py.swp new file mode 100644 index 0000000000000000000000000000000000000000..0bcb7bf8c62bbaf82434467cb362400eaeb4594f GIT binary patch literal 4096 zcmYc?2=nw+FxN9-00IF929<&zVeD2W49Q*$40(wq8Hsry3H$(}PB$krue1W6$~uTb z{o?$zlJdl&RF~A^%=A3{ko^1{r~C?C*RuSa(vr;lyu_kP$DH*1qRf(v++zJypm14g zd`W6WiC#e^KJ!QAMnhmU1n`9bFN3j>p#eyRvXY{Luuv#I#iMegAut*OqaiRF0;3@? T8UmvsFd71*Aut*O!z=^ Date: Fri, 6 May 2016 00:12:56 -0400 Subject: [PATCH 2/2] Create results.txt --- results.txt | 3 +++ 1 file changed, 3 insertions(+) create mode 100644 results.txt diff --git a/results.txt b/results.txt new file mode 100644 index 0000000..d5ebb85 --- /dev/null +++ b/results.txt @@ -0,0 +1,3 @@ +This toolbox has provided me with a basic understanding of what are and how to use genetic algorithms. Even though the cost function contains the target string, we can still learn how cost functions work. + +In terms of the mutation, given a small number of generations, it is very difficult to evolve past a certain number of letters. For example, let's look at at 26 character string, the alphabet, "ABCDEFGHIJKLMNOPQRSTUVWXYZ". If we run for 500 generations, we can only get a levenshtein distance of 2-5. If we run 1000 generations, we can get a levenshtein distance of 1-2. If we run 1500 generations, we almost always a levenshtein distance of 0, a the exact copy of the targe string.