Genetic Reductionism Definition

This is a cross-platform framework for using Genetic Algorithms for solutions. Written in Java and uses convinient plug-in features for every phase in the genetic development, while maintaining an easy-to-use API for easy integration into applications.

The Distributed Genetic Programming Framework is a scalable Java genetic programming environment. It comes with an optional specialization for evolving assembler-syntax algorithms. The evolution can be performed in parallel in any computer network.

Java API for implementing any kind of Genetic Algorithm and Genetic Programming applications quickly and easily. Contains a wide range of ready-to-use GA and GP algorithms and operators to be plugged-in or extended. Includes Tutorials and Examples.


Platforms: Windows, Mac, Linux

An object oriented library of an Genetic Algorithm, implemented in Java. Clear separation of the several concepts of the algorithm, e.g. Gene, Chromosome, Genotype, Phenotype, Population and Fitness Function. The fitness calculation is parallelized.


Platforms: Windows, Mac, Linux

An optimized java library for genetic algorithms. The library is designed to be fast and memory light, but still very easy to use.


Platforms: Windows, Mac, Linux

The Python Genetic Programming Project implements a Genetic Programming System a la J Koza in Python.


Platforms: Windows, Mac, Linux

This project provides a set of Python tools for creating various kinds of neural networks, which can also be powered by genetic algorithms using grammatical evolution. MLP, backpropagation, recurrent, sparse, and skip-layer networks are supported.


Platforms: Windows, Mac, Linux

Springbots is a python application which takes a set of 2d physical structures built with nodes and movable springs and evolve them for specific tasks like walking, swimming and jumping using genetic algorithm.


Platforms: Windows, Mac, Linux

Trilobots is an arcade-style shooter that evolves the abilities and programming of the enemies using a genetic algorithm. The end goal is to make the evolution transparent, allowing users to learn how genetic algorithms work while having fun.


Platforms: Windows, Mac, Linux

VKAS uses genetic programming methods to find out the relationship among a set of independent and dependent variable. It is a problem solver software which uses evolutionary computing methods.


Platforms: Windows, Mac, Linux

This script ensures that a name exists in a target namespace. If it does not, make it available in the target namespace using the given definition. The target should be a namespace dictionary (presumably for a module, see the discussion below otherwise). The default target is __builtins__...


Platforms: Windows, Mac, *nix, Python, BSD Solaris

M-files accompanying the " Genetic Algorithms & New Optimization Methods in MATLAB " webinar.These files provide what you need to run the two demos: Optimization of non-smooth objective function, and Optimization of a random stochastic objective function.To run the first demo run the file...


Platforms: Matlab

This zip file contains the Presentation (PDF) and M-files that were demonstrated in the MathWorks Webinar: Using Genetic Algorithms in Financial Applications delivered on Dec 11 2007.The purpose of the webinar was to highlight how Genetic Algorithms may be used to supplement portfolio...


Platforms: Matlab

This code proposes genetic algorithm (GA) to optimize the point-to-point trajectory planning for a 3-link (redundant) robotarm. The objective function for the proposed GA is to minimizing traveling time and space, while not exceeding a maximumpre-defined torque, without collision with any...


Platforms: Matlab

SpeedyGA is a vectorized implementation of a genetic algorithm in the Matlab programming language. Without bells and whistles, it faithfully implements the specification for a Simple GA given on pgs 10, 11 of M. Mitchell's GA book. See comments in code for details.This script has played a crucial...


Platforms: Matlab

We use the genetic algorithm (gatool) to determine the three parameters of the simple Antoine equation and the six parameters of the Modified Antoine Model. Predictions are in perfect agreement with experimental data of vapor pressure of ethanol versus temperature for a temperature range from...


Platforms: Matlab

The script allows to easily fit predefined complex analytical laws exploiting the potentiality of Genetic Algorithms.The script receives as input the handle to the analytic laws to be fitted to data. Such law may depend on multiple variables and several parameters. This optimization approach may...


Platforms: Matlab

These files are an adaptation of the ANOVA variance component estimators to be used in the analysis of genetic data, specifically Cockerham's 1969 Theta. Formulae were adapted from Sokal and Rohlf's 1995 Biometry, and test files from the book are given as reference.


Platforms: Matlab

Extended compact genetic algorithm (ECGA) is an algorithm that can solve hard problemsin the binary domain. ECGA is reliable and accurate because of the capability ofdetecting building blocks, but certain difficulties are encountered when we directly applyECGA to problems in the integer domain....


Platforms: Matlab

This particular hybrid genetic optimizer is referenced from: J Hu "Radio Frequency Front-End Measurement and Modeling," Ph.D. dissertation, North Carolina State University, Raleigh NC, 2011.It's used in fitting a RF power amplifier model to measured data and extracting the model parameters.


Platforms: Matlab