JGAP 3.1 reviewDownload
JGAP (pronounced "jay-gap") is a genetic algorithms component written in the form of a Java package
JGAP (pronounced "jay-gap") is a genetic algorithms component written in the form of a Java package. JGAP project provides basic genetic mechanisms that can be easily used to apply evolutionary principles to problem solutions. The ground is laid for introducing Genetic Programming to JGAP in the near future!
JGAP has been written to be very easy to use "out of the box," while also designed to be highly modular so that more adventurous users can easily plug-in custom genetic operators and other sub-components.
Genetic algorithms (GAs) are evolutionary algorithms that use the principle of natural selection to evolve a set of solutions toward an optimum solution. GAs are not only very powerful, but are also very easy to use as most of the work can be encapsulated into a single component, requiring users only to define a fitness function that is used to determine how "good" a particular solution is relative to other solutions.
What's New in This Release:
Improved architecture of grid architecture
Made ProgramChromosome implement Comparable
Moved common grid classes to org.jgap.distr.grid (previously they resided in the examples.grid package) and emphasized framework character of the relevant classes
Added setter for fitness evaluator to GPConfiguration
Added setters for crossover and selection method in GPConfiguration
Fixed bug in GPProgramFitnessComparator.compare
Fixed bug with Double.NaN in DefaultGPFitnessEvaluator
Added compareTo and equals methods to DefaultGPFitnessEvaluator
Fixed missing usage of IInitializer in Genotype.evolve that made it difficult subclassing Chromosome (see bug 1596231)
Fixed bug in Population.determineFittesChromosome (thanx to Knut)
Fixed bug in JGAPfactory.findHandlerFor
Added description to each test suite, it appears when running JUnit and makes debugging more fun
Added a lot of tests
Enhanced logic in DefaultCloneHandler and DefaultCompareToHandler
Fixed bug in BooleanGene.compareTo
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