Programming language to automatically generate programs by evolution (genetic programming).
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Evolu Lang

Evolu Lang is a programming language to automatically generate programs by evolution (genetic programming). Generator (genetic algorithm, particle swarm optimization or other) will use Evolu Lang to compile bytes with random mutations (gene) to program, run and test it.

It is created to be readable by human beings (instead of artificial neural networks) and easily editable and mixable for genetic algorithm (instead of tree structure and modern production languages).

How It Works

A developer defines commands by Evolu Lang to create a business specific language (or uses the standard commands pack) and defines tests (fitness), to determine what program he or she wants to create.

In the next step he or she uses a generator, which uses a genetic algorithm, particle swarm optimization or other evolutionary algorithms. In the simplest case: 1. Generator creates an array (population) with random bytes (genes). 2. It adds random changes (mutation) to each byte stream in this array. 3. It compiles each of these random byte streams by Evolu Lang and runs obtained programs with tests. 4. Bad programs will be deleted and best programs will be copied to the population. 5. Generator returns to step 2 until an obtained program passes all of the tests.


  • It is similar to usual programming languages with variables, commands, blocks and conditions.
  • Simple and explicit code. If you change one byte of code, you will change one command or parameter in program. If you just join two half parts of two different programs, you will get algorithm with properties of both parts.
  • Program is coded to a byte stream, so you can use a lot of libraries to mutate programs. Of course, you can use the string form for debug and research.
  • You are able to extend standard commands and conditions for the purposes of your task.
  • It has an interpreter in JavaScript, so you can create a distributed cluster from site visitors with a simple web page.

Language Philosophy

  • Explicit code. To control mutation, we must know, that when we change one byte, the algorithm will change slightly. When we copy a part of one algorithm to another, we expect, that the second algorithm will get some properties from the first one.
  • Everything makes sense. A mutation doesn’t know about syntax and formats. Interpreter must try to get maximum sense, from any byte stream. For example, if a byte can code 2 values, we must read even bytes as first value and odd values as second. So any byte value makes sense, not just the first two.
  • Simple structures. We can’t demand on the mutation placing all conditions in the beginning of a block. A better way is to mark conditions and expect them in any place of a block.



Each Evolu program starts with an EVOLU: prefix to check, that the file or stream contains a program.

Like XML, Evolu Lang is just a syntax format. So you need to have business-specific languages and mark, what language is used in this Evolu program. So, after the EVOLU: prefix, stream must contain language name and a colon.

<program> ::= "EVOLU:" <language> ":" <rules>

Language name is case insensitive and may contain any chars, except colon and space.

The genetic algorithm shouldn’t change these prefixes, they should be used only to store and transfer Evolu programs.


An Evolu program is split to separated blocks, rules, by separator. The separator is a built-in command and may be coded in different bytes (depending on command count, see “Commands and Parameters” section below). But in any languages 0x00 byte is a separator.

<rules>     ::= ( <rule> <separator> )*
<separator> ::= 0x00 | <separator bytes in this language>

Commands and Parameters

A rule contains pairs of commands and an optional parameter. Command byte begins with 0 bit and command number is encoded by next 7 bits. Any other bytes (beginning with 1) after command encode parameter number. For example, 2 bytes 1aaaaaaa and 1bbbbbbb encode parameter with aaaaaaabbbbbbb value.

<rule>      ::= ( <command> ( <parameter> )? )*
<command>   ::=   0xxxxxxx
<parameter> ::= ( 1xxxxxxx )*

There are 127 different commands number in one command byte, but language may have less commands. A mutation can generate any bytes and Evolu Lang must try to decode any of them. So, commands are marked numbers in a circle: if language have 3 commands (separator, a, b), 0 will be encode separator, 1 – a, 2 – b, but 3 will encode separator again, 4 – a, etc.

In language description commands may specify format of it’s parameter. Parameters can be unsigned integers (simple encoded by bits in parameter bytes) or list of values (encode in cycle, like commands).


There is special command type – condition. If all conditions in a rule are true, the rule’s commands will execute.

If a rule doesn’t have any conditions it will run once at start as constructor.

Standard Commands Pack

You can create your own language with Evolu Lang, but for common tasks it has the standard commands pack to create Turing completeness languages.


  • if_signal will be true, when program receives input signal (its name will be taken from parameter). If the rule contains several these conditions with different signals, all if_signal conditions will be true by any of these signals (because, program may receive only one signal at a moment).
  • if_var_more_0 will be true if variable (its name will be taken from condition parameter) will be more, than zero.


  • send_signal will send output signal (its name will be taken from parameter).
  • var_up will increase variable from parameter.
  • var_down will decrease variable from parameter.

The developer must define, what input and output signals will be in the language, but variables can be added dynamically by mutation.

How To

For example, we will generate program (by genetic programming), which calculates tick signals and on result signal it sends whether an even or an odd tick count it received.


Like XML, Evolu Lang is just a syntax format. So you need to define a language for your task using the evolu.lang.add(name, initializer) function. It receives a language name (to use it as a prefix in the source code for storing and transferring the program) and function (which adds the language commands to this), and returns a new language.

For the common cases you can use the standard commands pack, and you only need to define the input/output signals.

var lang = evolu.lang.add('EVEN-ODD', function() {
    this.add(evolu.lang.standard.input('tick', 'result'))
    this.add(evolu.lang.standard.output('even', 'odd'))


Get any genetic algorithm library or write it by yourself. Use a byte array (array of integers from 0 to 255, for example [0, 255, 13, 68, 145]) as genes.

var population = []
// Add 100 genes to the first population
for (var i = 0; i < 100; i++) {
    var gene = []
    // Each gene will have random length
    while (Math.random < 0.9) {
        // Add a random byte to the current gene
        gene.push(Math.round(255 * Math.random()))


Note that the integers in an array must be from 0 to 255.

In the genetic algorithm you can use any types of mutation for a byte stream (a lot of libraries contain them). You can add, change, delete and move bytes in the array.

You can use crossover to mix arrays or just move a part of bytes from one array to another (like horizontal gene transfer).


To calculate fitness for each gene in the population, you need to compile each byte array:

var program = lang.compile(population[i])

Send the data to the program and check its output data to calculate fitness. It’s like automatic unit testing, but your test must return a score, not just a pass/fail result.

If you use the standard commands pack, you can use the receive_signal event to listen output signals and the signal function to send input signals:

output = []
program.listen('receive_signal', function(signal) {

// Some hypothetical API

output = []


When you generate a program for your demands, you can save it to a disk or send to a server:

var source = bestProgram.toSource()

Source is a string with EVOLU: and a language name in prefix. For example, "EVOLU:EVEN-ODD:\x04\x80\x00\x01\x80\x03\x80\x05…".

Use evolu.lang.compile(string) to automatically find a language (using the source prefix) and compile the bytes into a program:

bestProgram == evolu.lang.compile(bestProgram.toSource())


  1. Install Rake (Ruby make) and RubyGems (Ruby package manager). For example, on Ubuntu:

    sudo apt-get install rake rubygems

  2. Install jasmin gem:

    gem install jasmin

  3. Run test server:

    rake jamsin

  4. Open http://localhost:8888.


Evolu Lang is licensed under the GNU Lesser General Public License version 3. See the LICENSE file or