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{{Short description|Java toolkit}}
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ECJ is a freeware [[evolutionary computation]] research system written in Java. It is a framework that supports a variety of evolutionary computation techniques, such as [[genetic algorithms]], [[genetic programming]], [[evolution strategies]], [[coevolution]], particle swarm optimization, and [[differential evolution]]. The framework models iterative evolutionary processes using a series of pipelines arranged to connect one or more subpopulations of individuals with [[Selection (genetic algorithm)|selection]], breeding (such as [[Crossover (genetic algorithm)|crossover]], and [[Mutation (genetic algorithm)|mutation]] operators that produce new individuals. The framework is open source and is distributed under the [[Academic Free License]]. ECJ was created by [http://www.cs.gmu.edu/~sean/ Sean Luke], a computer science professor at George Mason University, and is maintained by Sean Luke and a variety of contributors.

Features (listed from [http://cs.gmu.edu/~eclab/projects/ecj/ ECJ's project page]):

General Features:

* GUI with charting
* Platform-independent checkpointing and logging
* Hierarchical parameter files
* Multithreading
* Mersenne Twister Random Number Generators
* Abstractions for implementing a variety of EC forms.

EC Features:

* Asynchronous island models over TCP/IP
* Master/Slave evaluation over multiple processors
* Genetic Algorithms/Programming style Steady State and Generational evolution, with or without Elitism
* Evolutionary-Strategies style (mu, lambda) and (mu+lambda) evolution
* Very flexible breeding architecture
* Many selection operators
* Multiple subpopulations and species
* Inter-subpopulation exchanges
* Reading populations from files
* Single- and Multi-population coevolution
* SPEA2 multiobjective optimization
* Particle Swarm Optimization
* Differential Evolution
* Spatially embedded evolutionary algorithms
* Hooks for other multiobjective optimization methods
* Packages for parsimony pressure

GP Tree Representations:

* Set-based Strongly Typed Genetic Programming
* Ephemeral Random Constants
* Automatically Defined Functions and Automatically Defined Macros
* Multiple tree forests
* Six tree-creation algorithms
* Extensive set of GP breeding operators
* Seven pre-done GP application problem domains (ant, regression, multiplexer, lawnmower, parity, two-box, edge)

Vector (GA/ES) Representations:

* Fixed-Length and Variable-Length Genomes
* Arbitrary representations
* Five pre-done vector application problem domains (sum, rosenbrock, sphere, step, noisy-quartic)

Other Representations:

* NEAT
* Multiset-based genomes in the rule package, for evolving Pitt-approach rulesets or other set-based representations.

==See also==
* [[Paradiseo]], a metaheuristics framework
* [[MOEA Framework]], an open source Java framework for multiobjective evolutionary algorithms

==References==
* [http://cs.gmu.edu/~eclab/projects/ecj/ ECJ project page]
* Wilson, G. C. McIntyre, A. Heywood, M. I. (2004), [https://doi.org/10.1023%2FB%3AGENP.0000017053.10351.dc "Resource Review: Three Open Source Systems for Evolving Programs-Lilgp, ECJ and Grammatical Evolution"], ''Genetic Programming And Evolvable Machines'', '''5''' (19): 103-105, Kluwer Academic Publishers. ISSN 1389-2576

[[Category:Evolutionary computation]]
[[Category:Agent-based software]]
[[Category:Free software programmed in Java (programming language)]]

Java Evolutionary Computation Toolkit - Revision history

imported>El Goat-O: #suggestededit-add-desc 1.0