Release Notes: Greatly extended GP documentation. 12 new GP functions. Improved error handling in JGAPClientGP. Strongly improved grid computing functionality. A painted desert example (package examples.gp). SystemKit.printHelp(..) has been added. DefaultClientFeedback has been introduced. A bug in NumberKit.niceDecimalNumber, a bug in GP terminal False, and a bug in ColtRandomGenerator.nextInt() have been fixed. Test cases have been added.
Release Notes: The evolution cycle has been revamped and simplified for a better understanding. There are many smaller enhancements and architectural improvements, as well as some bugfixes. The MinimizingMakeChange example was simplified. Grid computing was improved. There are Javadoc enhancements and new JUnit tests.
Release Notes: Robocode 1.4.8 has been integrated. GP capabilities have been enhanced. Several bugs have been fixed. Logging of GP information has been enhanced. Javadoc has been enhanced. Some unit tests have been added.
Release Notes: JGAP was ported from Java 1.4 to Java 5. The architecture BaseChromosome and Chromosome was enhanced a lot. A breeder was introduced to simplify evolution outside or without Genotype --> grid. Grid logic was enhanced a lot. GP program generation was enhanced a lot. The evolution loop was enhanced. The speed of UTF-8 encoding was improved. CachedFitnessFunction was introduced. GPConfiguration was enabled for grid computing. ADF support in Genetic Programming was improved.
Release Notes: The grid logic and GP program generation have been enhanced a lot. The GP function ExchangeMemory and others have been added. GP program caching has been added to speed up evolution. GP TournamentSelector has been added. The static attribute has been removed from get/setGPConfiguration in the class GPGenotype. Matrixed memory has been added to the class Culture. Some bugs have been fixed. Unit tests have been added. Javadocs have been improved a lot, and some spelling errors have been fixed.
Release Notes: Genetic programming capabilities have been added. The classes are put into the package org.jgap.gp. An example can be found in the package examples.gp. Some unit tsts are available as well. This release has been made distributed by converting several fields to transient, making classes serializable, and using synchronized lists instead of pure ArrayLists. This release makes configuration serializable and marks some references in it as transient. The method Genotype.setActiveConfiguration has been removed.
Release Notes: Genetic programming capabilities were added. JGAP was made distributed by converting several fields to transient, making classes serializable, and using synchronized lists instead of pure ArrayLists. Configuration was made serializable, and some references in it were marked as transient. A check was done to ensure that certain properties (such as fitness function) can only be set once in the configuration for the current thread.
Release Notes: This release adds genetic programming capabilities. The classes are put into the package org.jgap.gp. An example can be found in the package examples.gp. This release has been made distributed by converting several fields to transient, making classes serializable, and using synchronized lists instead of pure ArrayLists. Configuration is serializable, and some references in it have been marked as transient. The abstract base classes org.jgap.BaseChromosome and org.jgap.BaseGeneticOperator have been added. getConfiguration has been added to interface IChromosome.
Release Notes: m_value (holding the allele) in Gene implementations is now private. Use getAllele and setAllele(Object) instead. The package org.jgap.impl.fitness has been added for classes related to fitness functions. There is a new org.jgap.JGAPTestCase abstract base class. All test cases now derived from this new class hosting common logic. There is a new org.jgap.util.NetworkKit ut class. A new example, examples.chromInit.ChromosomeInit, shows how to initialize chromosomes with different numbers of genes. There is a test suite for examples.
Release Notes: This release fixes a few bugs and adds some exciting new features, including oft-requested support for custom alleles and a more flexible event model. Please note that this is an alpha release and is not feature complete, not optimized, and probably contains bugs.