An object-oriented library in JavaScript to build modular and flexible cross-platform evolutionary algorithms

Department of Computer SciencesUniversity of Jaen (Spain)

Department of Computer's Architecture and TechnolgyUniversity of Granada (Spain)

Victor M. Rivas Juan J. Merelo, Gustavo Romero, Maribel García Arenas, Antonio Mora García

The GeNeura Team's Evolutionary Object Libraries Family

1990's EO C++

2000'sJEO Java

OPEAL Perl

C++

2010'sjsEO

Javascriptnodeo

“Any object that can be attached some kind of fitness value is a potential candidate for evolution.”

github.com/vrivas/jsEO

√ Portability: 99,99% Navigator+OS

√ Trivially “installed” and executed

x Slow

x Low amount of computer resources

<<abstract>>jsEO

<<abstract>>jsEOIndividual

jsEOPopulation

<<abstract>>jsEOAlgorithm

<<abstract>>jsEOOperator

Makes to evolve

Uses

Is composed of

jsEO's Class Diagram: Core package

jsEOGetIndividual

jsEOSendIndividual

Distributed island model

X

Server

EAs are executed in many different navigators that run under many differents operating systems

installed in many different hardware devices

Best LOCAL individual

Best GLOBAL individual

Experiments and Results

256-bit Royal Road function128-real terms equation

Executed just accesing:jseo.vrivas.es

Two problems

Population size: 500Tournament size: 2Generations: 50Crossover rate: 0.73Mutation rate: 0.18Requesting individual rate: 0.09Genes affected by mutation: 1%Indiv. replaced per generation: 50%

(Only for the 128-term equation problem)Range for new real values: (-10,10)

A single configuration

In about 24 hours, volunteer recruited from social networks visited the URL and ran the GA

256-bit Royal Road: 359 exec by 279 visitors, computing 3,952,000 evaluations128-real terms equation: 304 exec by 271 visitors, computing 4,667,000 evaluations

More than 300 executions

Browsers Operating Systems

w w

w .

g e

n e

u r

a . o

r g