github.com/they4kman/experimentation/machine-learning/genetic-algorithms

Genetic Arithmetic Expression Solver

Execute python genetic_expr_ui.py to get a graphical interface.

Description: a number is randomly chosen, and the aim of the program is to drum up a simple arithmetic equation using only addition, subtraction, multiplication, and division of a number of components less than 10. For instance, for the number 184, a solution might be 6*7*4+1-5+8+7+5.

To find its solutions, the program begins with a population of 30 "chromosomes", each consisting of 30 "genes" representing digits or operators. At each step, two chromosomes are chosen at random-ish. We roll a die to see if we should crossover them, which is to swap their bits around a random bit

The program defines a simple language with characters defined as 4-bit nibbles:

Index	Binary	Character
0	0000	0
1	0001	1
2	0010	2
3	0011	3
4	0100	4
5	0101	5
6	0110	6
7	0111	7
8	1000	8
9	1001	9
10	1010	+
11	1011	-
12	1100	*
13	1101	/
14	1110	Invalid
15	1111	Invalid

These are called genes. A chromosome is a list of genes. In the demonstration, we use chromosomes with 30 genes.

TODO