A Genetic Algorithm AI lib for JS
npm install genetics-ai.js``bash`
npm install genetics-ai
Here we will use the DNA (now replaced as genome) to refer to the Genetics AI configuration.
The gnome is a sequence of bases that may be connections or biases type.
The connections are the links between sensors, neurons and actions, and the biases are the neurons and actions bias.
You will have to extend the Individual class and implement the fitness method.
`js
import { Individual } from 'genetics-ai'
class Car extends Individual {
constructor(...args) {
super(...args)
this.health = 100
}
fitness() {
return this.health / 100
}
}
`
The genome is a sequence of bases as a sequence of 3 or 5 digits.
Each digit is a base 32 number to make the genome more compact. To explore the most of the data structure, we will use the binary of its digits.
`js`
const base = "000"
| config | target |
|-------:|------------:|
| 0 | 00 |
| 00000 | 00000 00000 |
config | data
0 0 0 0 0 | 0 0 0 0 0 0 0 0 0 0
|-----| |
| base type
| 0 - connection
| 1 - bias
saved data
This is the base that connects sensors, neurons and actions.
It has 5 digits, the first one is the config, the second and third ones are the source and the fourth and fifth ones are the target.
#### Example 1
`js`
const base = "00000"
| config | source | target |
|-------:|------------:|------------:|
| 0 | 00 | 00 |
| 00000 | 00000 00000 | 00000 00000 |
Sources can be sensors (0) or neurons (1).
Targets can be neurons (0) or actions (1).
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|-----| |
| base type = 0 --> type = connection
aditional data = 0000 --> weight = 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|---------------| |
| source type = 0 --> source = sensor
| 0 - sensor
| 1 - neuron
source id = 000000000 --> sensor id = 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|---------------| |
| target type = 0 --> target = neuron
| 0 - neuron
| 1 - action
target id --> neuron id = 0
#### Example 2
`js`
const base = "A0B0C"
| config | source | target |
|-------:|------------:|------------:|
| A | 0B | 0C |
| 01010 | 00000 01011 | 00000 01100 |
0 1 0 1 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 1 1 0 0
|-----| |
| base type = 0 --> type = connection
aditional data = 0101 --> weight = 50 1 0 1 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 1 1 0 0
|---------------| |
| source type = 1 --> source = neuron
source id = 000000101 --> source id = 50 1 0 1 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 1 1 0 0
|---------------| |
| target type = 0 --> target = neuron
target id = 000000110 --> target id = 6
You may have at most:
- 512 Sensors
- 512
- 512
The weight is between [0, 15].
| config | source | target |
|-------:|------------:|------------:|
| U | VU | VU |
| 11110 | 11111 11110 | 11111 11110 |
| U | VV | VV |
| 11110 | 11111 11111 | 11111 11111 |
Highest sensor into the highest neuron:
1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0
|-----| |
| base type = 0 --> type = connection
aditional data = 1111 --> weight = 151 1 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0
|---------------| |
| source type = 0 --> source = sensor
source id = 111111111 --> source id = 5111 1 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0
|---------------| |
| target type = 0 --> target = neuron
target id = 111111111 --> target id = 512
Highest neuron into the highest action:
1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
|-----| |
| base type = 0 --> type = connection
aditional data = 1111 --> weight = 151 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
|---------------| |
| source type = 1 --> source = neuron
source id = 111111111 --> source id = 5111 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
|---------------| |
| target type = 0 --> target = action
target id = 111111111 --> target id = 512
This base set the bias of a sensor, neuron or action.
It has 3 digits, the first one is the config, the second and third ones are the target.
Bias bases are accumulative!
`js`
const base = "100"
| config | target |
|-------:|------------:|
| 1 | 00 |
| 00001 | 00000 00000 |
0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
|---| | |
| | base type = 0 --> type = connection
| | 0 - connection
| | 1 - bias
| negative sign --> positive = 0
| 0 - positive
| 1 - negative
aditional data = 000 --> bias = 00 0 0 0 1 0 0 0 0 0 0 0 0 0 0
|-------------| |-|
| |
| target type = 00 --> target = sensor
| 00 - sensor
| 01 - neuron
| 10 - action
| (11 - neuron)
target id = 00000000 --> sensor id = 0
You may set bies at most:
- 255 Sensors
- 255
- 255
The bias` is between [-7, 7].
| config | target | |
|-------:|------------:|:----------------------------|
| V | VS | bias with -7 for sensor 255 |
| 11111 | 11111 11100 |
| V | VT |
| 11111 | 11111 11101 |
| V | VU |
| 11111 | 11111 11110 |
| V | VV |
| 11111 | 11111 11111 |
1 1 1 1 0 1 1 1 1 1 1 1 1 0 0
|---| | |
| | base type = 0 --> type = bias
| negative sign --> negative = 1
aditional data = 111 --> bias = -71 1 1 1 0 1 1 1 1 1 1 1 1 0 0
|-------------| |-|
| target type = 00 --> target = sensor
target id = 11111111 --> target id = 255
| b10 | b32 | bin |
|:---:|:---:|:-----:|
| 0 | 0 | 00000 |
| 1 | 1 | 00001 |
| 2 | 2 | 00010 |
| 3 | 3 | 00011 |
| 4 | 4 | 00100 |
| 5 | 5 | 00101 |
| 6 | 6 | 00110 |
| 7 | 7 | 00111 |
| 8 | 8 | 01000 |
| 9 | 9 | 01001 |
| 10 | A | 01010 |
| 11 | B | 01011 |
| 12 | C | 01100 |
| 13 | D | 01101 |
| 14 | E | 01110 |
| 15 | F | 01111 |
| 16 | G | 10000 |
| 17 | H | 10001 |
| 18 | I | 10010 |
| 19 | J | 10011 |
| 20 | K | 10100 |
| 21 | L | 10101 |
| 22 | M | 10110 |
| 23 | N | 10111 |
| 24 | O | 11000 |
| 25 | P | 11001 |
| 26 | Q | 11010 |
| 27 | R | 11011 |
| 28 | S | 11100 |
| 29 | T | 11101 |
| 30 | U | 11110 |
| 31 | V | 11111 |