Hide Comments
Hide Comments

Comments (0)

Represents namespace RSGAConsts.

expandingClasses

 

Name

Description

public class

EGAException

Defines the base exception class for the entire Genetic Algorithms Component Library

public class

EGPException

Defines the base exception class for the genetic programming portion of the library
 

public class

TGAFitness

Defines the fitness type for the Genetic Algorithms Component Library

public class

TGAFloat

Defines the floating point type for the Genetic Algorithm Component Library

public class

TGAProbability

Defines the numeric type for representing probabilities in the Genetic Algorithms Component Library, including CrossoverProbability, MutationProbability, and InversionProbability.

Top

expandingEnumerations

 

Name

Description

public enumeration

TExecutionLimit

Defines the execution limit for the virtual machine

public enumeration

TExecutionState

Defines the execution state for a virtual machine

public enumeration

TGACrossoverMethod

Defines the different crossover boundaries that can be used in recombination (combining parts of two parent's chromosome to create a new chromosome) for the TRSCustomGeneticAlgorithm component

Crossover is one of the evolutionary biology techniques used by the genetic algorithm component, along with inheritance, mutation, and selection. In crossover, the genetic algorithm component splices out the first random n-bits of one parent and concatenates it with the last chromosomesize-n bits of the other parent. The chromosome size of the child is the same as its parents. The Crossover Method property controls how the break is selected: on a gene boundary, bit boundary, or byte, word, or longword boundary. Note that crossover on a non-gene boundary could possibly cause invalid gene values because the newly combined gene at the crossover point is a random mixture of bits from the 2 parents.
 

public enumeration

TGAFitnessMethod

Defines the type of fitness methods. It controls how the genetic algorithm component evolves: should it seek to maximize fitness or minimize fitness?
 

public enumeration

TGAGeneticOperation

Defines the types of genetic Operations that the genetic component performs.

Genetic algorithms and programs are computer science techniques that seek to solve optimization or search problems. They are inspired by evolutionary biology and approach the search problem as a task of evolving a group or population of candidate individuals through successive generations, selecting fitter (or better) child individuals for each generation, until a solution is found. It uses evolutionary biology techniques such as inheritance, mutation, selection, and crossover (also called recombination).
 

public enumeration

TGASelectionMethod

Defines how the genetic component selects individuals from the current generation to be used as parents of the next generation

public enumeration

TGeneType

Defines the simple types that can be used for Genes in the genetic algorithm component.

public enumeration

TGPBloatStrategy

Defines the strategies for combatting bloat (program growth without (significant) return in terms of fitness.) in genetic programming

public enumeration

TGPCrossoverMethod

Defines the crossover method used in genetic programming

public enumeration

TGPGeneticInstruction

Defines the type of genetic instructions (and tree nodes) in a genetic program

public enumeration

TGPInitializationMethod

Defines the initialization methods for initializing a genetic program tree.

public enumeration

TGPMutationMethod

Defines the different mutation methods the genetic programming component can perform

noteNote

Point mutation is listed for completeness. However, with our engine it can happen as inversion as well. If point mutation is done as Inversion, its probability is controlled by the InversionProbability property. If point mutation is done as a mutation method, its probability is controlled by the MutationProbability and the MutationMethodWeights.

public enumeration

TGPPointMutationMethod

Defines how often the genetic programming component attemps point mutation in a tree

Top

expandingTypes

 

Name

Description

public type

TExecutionStates

Defines the set of execution state for a virtual machine

public type

TGAFitnessArray

Defines a dynamic array of Fitness values

public type

TGAGeneticOperations

Defines the set of genetic operations

public type

TGAProbabilityArray

Defines a dynamic array type of probabilities

public type

TGAProbabilityTable

Defines a dynamic table type of probabilities

public type

TGPGeneticInstructions

Defines the set of genetic instruction types (and tree nodes) in a genetic program

public type

TGPMutationMethodWeights

Defines the weights or probabilities that a particular mutation method will be chosen from the set of genetic programming mutation methods

public type

TIntegerArray

Represents an array of the Integer type.

Top

expandingVariables

 

Name

Description

public variable

CROSSOVER_PROBABILITY

Default Crossover Probability for genetic algorithms

public variable

DEFAULT_ADAPTION_SAMPLE_SIZE

Default percentage of population to use as a sample for adapting heuristics

public variable

DEFAULT_DIVERSITY_LIMIT

Default Diversity Limit for genetic components

public variable

DEFAULT_ELITIST_PCT

Default Elitist Percentage for genetic components

public variable

DEFAULT_FITNESS_CUTOFF

Default Fitness Cutoff for genetic components

public variable

DEFAULT_PARSIMONY_COEFFICIENT

Default Parsimony Coefficient used in bloat control for genetic programming

public variable

DEFAULT_TARPEIAN_PROBABILITY

Default Tarpeian probability used in bloat control for genetic programming

public variable

GP_CROSSOVER_PROBABILITY

Default Crossover Probability for genetic programming

public variable

INVERSION_PROBABILITY

Default Inversion Probability for genetic components

public variable

MUTATION_PROBABILITY

Default Mutation Probability for genetic components

public variable

NONTERMINALS_SELECTION_PROBABILITY

Default probability that non-terminals (functions) will be selected for genetic operations in genetic programming

Top

expandingConstants

 

Name

Description

public constant

DefaultDuplicatesRetries

Default number of attempts to retry creating an individual on initialization

public constant

DefaultMutationWeights

Default Mutation Weights/Probabilities for genetic programming

public constant

Default_Genetic_Operations

Default genetic operations to perform in genetic components

public constant

DEFAULT_INIT_POPULATION

Default initial population size for genetic components

public constant

DEFAULT_ITERATION_LENGTH

Default number of generations before adapting heuristics

public constant

FinishedStates

Finished states for virtual machine

public constant

SGACLNag

'We hope you are enjoying the evaluation version of the Genetic Algorithms Component Library.'+sLineBreak+'To order the GACL, please go to www.RiverSoftAVG.com'

public constant

SInstructionNotUnique

'instruction name must be unique'

public constant

SInvalidInstructionIndex

'%i is an invalid instruction set encoding'

public constant

SInvalidNumInstructionArgs

'Invalid number of arguments (%d) for "%s" instruction'

public constant

SInvalidOperationCode

'INVALID OPERATION'

public constant

SInvalidTerminalNode

'Invalid terminal node. Node requires greater than 0 children'

public constant

SMissingGeneticProgram

'Missing Genetic Program Engine'

public constant

SMissingVirtualMachine

'Missing Virtual Machine'

public constant

SNoConstantMutation

'No constant mutation function defined'

public constant

SNodeFull

'Node cannot accept anymore children'

public constant

SNoEnumerationFound

'No enumerated value found in chromosome'

public constant

SNoFitnessFunction

'No fitness function defined'

public constant

SNoInstructionAssigned

'No instruction assigned to node'

public constant

SNoInstructionsFound

'No nodes found'

public constant

SNoOperationsFound

'No operations found'

public constant

SNoSelectionFunction

'No custom selection function defined'

public constant

SNoTerminalsFound

'No terminals found'

public constant

SUnknownInstruction

'Unknown instruction "%s"'

public constant

SValueNotEnumeration

'"%s" is not a valid enumerated value'

Top

Comments (0)