Algorithm-Evolutionary

Classic bitstring individual for evolutionary computation; usually called chromosome, and using a different implementation from Algorithm::Evolutionary::Individual::BitString

Algorithm::Evolutionary::Individual::String

A character string to be evolved. Useful mainly in word games

Algorithm::Evolutionary::Individual::Tree

A Direct Acyclic Graph, or tree, useful for Genetic Programming-Style stuff

Algorithm::Evolutionary::Individual::Vector

Array as an individual for evolutionary computation

Algorithm::Evolutionary::Op::Animated_GIF_Output

Creates an animated GIF, a frame per generation. Useful for binary strings.

Algorithm::Evolutionary::Op::ArithCrossover

Arithmetic crossover operator; performs the average of the n parents crossed

Algorithm::Evolutionary::Op::Base

Base class for Algorithm::Evolutionary operators,

Algorithm::Evolutionary::Op::Bitflip

Bit-flip mutation

Algorithm::Evolutionary::Op::Breeder

Even more customizable single generation for an evolutionary algorithm.

Algorithm::Evolutionary::Op::Breeder_Diverser

Like Breeder, only it tries to cross only individuals that are different

Algorithm::Evolutionary::Op::CX

Algorithm::Evolutionary::Op::CanonicalGA

Canonical Genetic Algorithm, with any representation

Algorithm::Evolutionary::Op::Canonical_GA_NN

Canonical Genetic Algorithm that does not rank population

Algorithm::Evolutionary::Op::ChangeLengthMutation

Increases/decreases by one atom the length of the string

Algorithm::Evolutionary::Op::Combined

Combinator of several operators of the same arity, unary or binary

Algorithm::Evolutionary::Op::Convergence_Terminator

Checks for termination of an algorithm, returns true if a certain percentage of the population is the same

Algorithm::Evolutionary::Op::Creator

Operator that generates groups of individuals, of the intended class

Algorithm::Evolutionary::Op::Crossover

n-point crossover operator; puts fragments of the second operand into the first operand

Algorithm::Evolutionary::Op::DeltaTerm

Termination condition for an algorithm; checks that the difference of the best to a target is less than a delta

Algorithm::Evolutionary::Op::EDA_step

Single step for a Estimation of Distribution Algorithm

Algorithm::Evolutionary::Op::Easy

evolutionary algorithm, single generation, with variable operators.

Algorithm::Evolutionary::Op::Easy_MO

Multiobjecttive evolutionary algorithm, single generation, with variable operators

Algorithm::Evolutionary::Op::Eval::General

General and simple population evaluator

Algorithm::Evolutionary::Op::Eval::MO_Rank

Multiobjective evaluator based on Pareto rank

Algorithm::Evolutionary::Op::FullAlgorithm

Skeleton class for a fully-featured evolutionary algorithm

Algorithm::Evolutionary::Op::GaussianMutation

Changes numeric chromosome components following the gaussian distribution.

Algorithm::Evolutionary::Op::Gene_Boundary_Crossover

n-point crossover operator that restricts crossing point to gene boundaries

Algorithm::Evolutionary::Op::GeneralGeneration

Customizable single generation for an evolutionary algorithm.

Algorithm::Evolutionary::Op::Generation_Skeleton

Even more customizable single generation for an evolutionary algorithm.

Algorithm::Evolutionary::Op::GenerationalTerm

Checks for termination of an algorithm.

Algorithm::Evolutionary::Op::IncMutation

Increments/decrements by one the value of one of the components of the string, takes into account the char class

Algorithm::Evolutionary::Op::Inverover

Michalewicz's inver-over Operator.

Algorithm::Evolutionary::Op::LinearFreezer

Used by Simulated Annealing algorithms, reduces temperature lineally.

Algorithm::Evolutionary::Op::Mutation

Bitflip mutation, changes several bits in a bitstring, depending on the probability

Algorithm::Evolutionary::Op::NoChangeTerm

Checks for termination of an algorithm; terminates when several generations transcur without change

Algorithm::Evolutionary::Op::Novelty_Mutation

Mutation guaranteeing new individual is not in the population

Algorithm::Evolutionary::Op::Permutation

Per-mutation. Got it?

Algorithm::Evolutionary::Op::Population_Output

Flexible population printing class

Algorithm::Evolutionary::Op::QuadXOver

N-point crossover operator that changes operands

Algorithm::Evolutionary::Op::Quad_Crossover_Diff

Uniform crossover, but interchanges only those atoms that are different

Algorithm::Evolutionary::Op::Replace_Different

Incorporate individuals into the population replacing the worst ones but only if they are different.

Algorithm::Evolutionary::Op::Replace_Worst

Incorporate individuals into the population replacing the worst ones

Algorithm::Evolutionary::Op::RouletteWheel

Fitness-proportional selection, using a roulette wheel.

Algorithm::Evolutionary::Op::Selector

Abstract base class for population selectors

Algorithm::Evolutionary::Op::SimulatedAnnealing

An operator that performs the simulated annealing algorithm on an individual, using an external freezing schedule

Algorithm::Evolutionary::Op::Storing

Applies the op and keeps the result

Algorithm::Evolutionary::Op::StringRand

randomly change chars in a string

Algorithm::Evolutionary::Op::String_Mutation

Single character string mutation

Algorithm::Evolutionary::Op::Tournament_Selection

Tournament selector, takes individuals from one population and puts them into another

Algorithm::Evolutionary::Op::TreeMutation

GP-like mutation operator for trees

Algorithm::Evolutionary::Op::Uniform_Crossover

interchanges a set of atoms from one parent to the other.

Algorithm::Evolutionary::Op::Uniform_Crossover_Diff

Uniform crossover, but interchanges only those atoms that are different

Algorithm::Evolutionary::Op::VectorCrossover

Crossover for Algorithm::Evolutionary::Individual::Vector.

Algorithm::Evolutionary::Run

Class for setting up an experiment with algorithms and population

Algorithm::Evolutionary::Utils

Container module with a hodgepodge of functions

Algorithm::Evolutionary::Wheel

Random selector of things depending on probabilities

Other files

To install Algorithm::Evolutionary, copy and paste the appropriate command in to your terminal.

cpanm

cpanm Algorithm::Evolutionary

CPAN shell

perl -MCPAN -e shell
install Algorithm::Evolutionary

For more information on module installation, please visit the detailed CPAN module installation guide.

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