Search Results for "evolution"

popt4jlib is an open-source parallel optimization library for the Java programming language supporting both shared memory and distributed message passing models. Implements a number of meta-heuristic algorithms for Non-Linear Programming, including Genetic Algorithms, Differential Evolution, Evolutionary Algorithms, Simulated Annealing, Particle Swarm Optimization, Firefly Algorithm, Monte-Carlo Search, Local Search algorithms, Gradient-Descent-based algorithms, as well as some well-known network flow and other graph algorithms. A fast parallel implementation of the network simplex method, and some full-fledged parallel/distributed MIP solvers will be added in the next version. ...

Opt4J is an open source Java-based framework for evolutionary computation. It contains a set of (multi-objective) optimization algorithms such as evolutionary algorithms (including SPEA2 and NSGA2), differential evolution, particle swarm optimization, and simulated annealing. The benchmarks that are included comprise ZDT, DTLZ, WFG, and the knapsack problem. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary meta-heuristic optimization algorithms. For this purpose, Opt4J relies on a module-based implementation and offers a graphical user interface for the configuration as well as a visualization of the optimization process.

This cellular automation simulation uses probability to control the growth and decay of different cells. This simulation uses cells of 6 different colors each of which is initially given one cell to be placed in a random location on the grid. 3 rules govern the evolution of this system: First, each cell will randomly select an empty cell around it or itself. If an empty cell is selected, a new cell will be formed in it. If the cell selects itself, it will not expand. In the next iteration, the new cells follow the same process. Second, every color is predestined to consume another color if the two make contact. ...

The MOEA Framework is a free and open source Java library for developing and experimenting with multiobjective evolutionary algorithms (MOEAs) and other general-purpose multiobjective optimization algorithms. The MOEA Framework supports genetic algorithms, differential evolution, particle swarm optimization, genetic programming, grammatical evolution, and more. A number of algorithms are provided out-of-the-box, including NSGA-II, NSGA-III, ε-MOEA, GDE3 and MOEA/D. In addition, the MOEA Framework provides the tools necessary to rapidly design, develop, execute and statistically test optimization algorithms.

Bellman, named after the character in Lewis Carroll's The Hunting of the Snark, is a program for searching for catalytic interactions in Conway's Game of Life and potentially other similar cellular automata. Results are derived directly from the automaton's evolution rule, not generated from a list of candidate catalysts as with previous searchers.

A base for programs. Includes algorythms for Q-learning and SOM's etc. too. Examples: Hamron: Simulates evolution, uses the 2D-renderer. DriveUnit: created for school, for a robotic arm, uses the 3D-renderer. Hlearn: http://www.sagenb.org/home/pub/8

This utility, lingen, implements evolution of native machine code via linear genetic programming. The assembly level code uses a subset of assembly language which manipulates and performs calculations using the floating point unit (FPU) of the CPU.

MooGraph is an utility to produce interactive dynamical graphs from statistical data. Deliberately inspired to GapMinder, it represents the evolution of multivariate data in time by means of coloured bubbles of variable sizes on an (x,y) plot.

Kandid generates images using genetic algorithms. In a simulated evolution surprising images can be found calculated with Lisp expressions, Textures, Iterated Function Systems, Linear Cellular Automata, Voroni diagrams, Lindenmayer Systems and POVray

JRVFSim (Jarvis) is a simulator of a fluid dynamics phenomenon known as radial viscous fingering. Its main feature consists of taking jordan curves and simulating their evolution subject to various parameters. Includes a partial API for numerical methods

The genesis-ai project is an attempt to develop complex neural network behavior by means of evolutionary techniques.