cart::Add< T >  
Tree::Primitives::AddT< T >  Add function primitive (Tree genotype) 
AlgAEliGpea  Asynchronous elimination global parallel algorithm 
AlgAEliGpea2  Asynchronous elimination global parallel algorithm (outdated version) 
AlgNSGA2  
Algorithm  Algorithm base class 
AlgSGenGpea  Synchronous generational global parallel algorithm 
cart::And< T >  
And  
And2  
AntEvalOp  Artificial ant evaluation class (and environment simulator) 
ArtificialBeeColony  Artificial Bee Colony algorithm (see e.g. http://www.scholarpedia.org/article/Artificial_bee_colony_algorithm)ABC algorithm accepts only a single FloatingPoint genotype (vector of real values). Additionally, it adds the following genotype for algorithm implementation:
 FloatingPoint genotype as trial (a cycle counter for each individual)

BitString::BalancedMutOp  
Binary::Binary  Binary class  implements genotype as a vector of binary coded real values with variable interval and precision 
Binary::BinaryCrsHalfUniform  Binary genotype: half uniform crossover operator 
Binary::BinaryCrsMasked  Binary genotype: masked crossover operator. Described on http://www.tomaszgwiazda.com/maskedX.htm. Evolve only one child instead of two as described online 
Binary::BinaryCrsNonGeometric  Binary genotype: non geometric crossover operator 
Binary::BinaryCrsOnePoint  Binary genotype: one point crossover operator 
Binary::BinaryCrsRandomRespectful  Binary genotype: random respectful crossover operator. Described on http://www.tomaszgwiazda.com/RandomRX.htm. Evolve only one child instead of two as described online 
Binary::BinaryCrsReducedSurrogate  Binary genotype: reduced surrogate crossover operator 
Binary::BinaryCrsSegmented  Binary genotype: segmented crossover operator 
Binary::BinaryCrsShuffle  Binary genotype: shuffle crossover operator 
Binary::BinaryCrsTwoPoint  Binary genotype: two point crossover operator 
Binary::BinaryCrsUniform  Binary genotype: uniform crossover operator 
Binary::BinaryMutMix  Binary genotype: mixing mutation operator 
Binary::BinaryMutSimple  Binary genotype: simple (bitflip) mutation operator 
BitEvalOp  
BitString::BitString  BitString class  implements genotype as a series of bits 
BitString::BitStringCrsOnePoint  BitString genotype: one point crossover operator 
BitString::BitStringCrsUniform  BitString genotype uniform crossover operator 
BitStringHillClimbing  
BitString::BitStringMutMix  BitString genotype mixing mutation operator 
BitString::BitStringMutSimple  BitString genotype simple (one bit) mutation operator 
BoolV  
cart::Cartesian  
cart::CartesianCrsOnePoint  Cartesian genotype: one point crossover operator 
cart::CartesianMutOnePoint  Cartesian genotype: one point mutation operator 
Classifier  Classifier class that holds all parameters and pointer to individual to which the parameters belong 
ClassifierParams  Classifier data structure in XCS algorithm 
Clonalg  Clonal Selection Algorithm (see e.g. http://en.wikipedia.org/wiki/Clonal_Selection_Algorithm).This CLONALG implements:
 cloning Versions:
 static cloning : n of the best antibodies are cloned beta*populationSize times
 proportional cloning: number of clones per antibody is proportional to that ab's fitness
 inversely proportional hypermutation : better antibodies are mutated less
 selectionSchemes:
 CLONALG1  at new generation each antibody will be substituded by the best individual of its set of beta*population clones
 CLONALG2  new generation will be formed by the best (1d)*populationSize clones ( or all if the number of clones is less than that )
 birthPhase: where d * populationSize of new antibodies are randomly created and added to the population for diversification

Comm::Communicator  Communicator class for interprocess communication 
Tree::Primitives::Cos  Cos function primitive (Tree genotype) 
cart::Cos< T >  
Crossover  Crossover class  handles crossover of _individuals_ (as opposed to CrossoverOp class that crosses genotypes) 
CrossoverOp  CrossoverOp base class 
CuckooSearch  Cuckoo search (CS) optimization algorithm (see http://en.wikipedia.org/wiki/Cuckoo_search)CS algorithm accepts only FloatingPoint genotype (vector of real values). This implementation is based on: http://www.mathworks.com/matlabcentral/fileexchange/29809cuckoosearchcsalgorithm 
Deme  Deme class  inherits a vector of Individual objects 
DifferentialEvolution  Differential evolution (DE) optimization algorithm (see e.g. http://en.wikipedia.org/wiki/Differential_evolution)DE algorithm accepts only a single FloatingPoint genotype (vector of real values) 
cart::Div< T >  
DivInt  
Tree::Primitives::DivT< T >  Div function primitive (Tree genotype) 
Elimination  Elimination (generation gap) algorithm with roulette wheel elimination selection operatorThis algorithm is genotype independent (it can be used with any Genotype) 
Environment  Environment for the XCS algorithm 
Tree::Primitives::ERC< T >  Ephemereal random constant (ERC) node class (Tree genotype) 
Tree::Primitives::ERCD  Ephemereal random constant (ERC) node of type double (Tree genotype) 
EvalOp  
EvaluateOp  Evaluation base class 
EvolutionContext  Evolutionary context class 
EvolutionStrategy  (mu/rho +/, lambda)  Evolution Strategy (ES) algorithm.This algorithm is genotype independent (it can be used with any Genotype) 
Fitness  Fitness base class 
FitnessMax  Fitness for maximization problems 
FitnessMin  Fitness for minimization problems 
FloatingPoint::FloatingPoint  FloatingPoint class  implements genotype as a vector of floating point values 
FloatingPoint::FloatingPointCrsArithmetic  FloatingPoint genotype: offspring is defined as a linear combination of two vectors 
FloatingPoint::FloatingPointCrsArithmeticSimple  FloatingPoint genotype: take recombination point k. Child 1 is parent1 until k, rest is arithmetic average of parents 
FloatingPoint::FloatingPointCrsArithmeticSingle  FloatingPoint genotype: take random allele k. That point is arithmetic average of parents, other points are from parents 
FloatingPoint::FloatingPointCrsAverage  FloatingPoint genotype: child is average value of parent genes 
FloatingPoint::FloatingPointCrsBga  FloatingPoint genotype: BGA crossover (http://bib.irb.hr/datoteka/640222.CEC_2013.pdf, http://sci2s.ugr.es/publications/ficheros/IJIS2003183309338.PDF) 
FloatingPoint::FloatingPointCrsBlx  FloatingPoint genotype: value on allele i is random value taken from minmax interval from parents plus/minus difference times rand 
FloatingPoint::FloatingPointCrsBlxAlpha  FloatingPoint genotype: BLX alpha crossover (http://bib.irb.hr/datoteka/640222.CEC_2013.pdf) 
FloatingPoint::FloatingPointCrsBlxAlphaBeta  FloatingPoint genotype: BLX alphabeta crossover (http://bib.irb.hr/datoteka/640222.CEC_2013.pdf) 
FloatingPoint::FloatingPointCrsDiscrete  FloatingPoint genotype: allele value for each gene is either from parent1 or from parent2 with equal probability 
FloatingPoint::FloatingPointCrsFlat  FloatingPoint genotype: value on allele i is random value taken from minmax interval from parents 
FloatingPoint::FloatingPointCrsHeuristic  FloatingPoint genotype: value on allele i smaller gene value + rand value * (greater  smaller value) 
FloatingPoint::FloatingPointCrsLocal  FloatingPoint genotype: local crossover (http://bib.irb.hr/datoteka/640222.CEC_2013.pdf) 
FloatingPoint::FloatingPointCrsOnePoint  FloatingPoint genotype: one point crossover operator with permissible split points only between dimensions 
FloatingPoint::FloatingPointCrsRandom  FloatingPoint genotype: random crossover, for testing purposes 
FloatingPoint::FloatingPointCrsSbx  FloatingPoint genotype: SBX crossover (http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.33.7291&rep=rep1&type=pdf, http://www.iitk.ac.in/kangal/papers/k2011017.pdf) 
FloatingPoint::FloatingPointMutSimple  FloatingPoint genotype: simple mutation where a single vector element is mutated. New value is random value from the given domain 
cart::Function  
FunctionMaxEvalOp  
FunctionMinEvalOp  Function minimization evaluation class 
cart::FunctionSet  
GeneticAnnealing  Genetic annealing algorithm (see e.g. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.7606, http://drdobbs.com/architectureanddesign/184409333?pgno=10)Currently implemented only for minimization problems! 
GenHookeJeeves  New algorithm, in development 
Genotype  Genotype base class 
HallOfFame  Records a set of bestsofar individuals 
If  
IfFoodAhead  GP function, checks if the food is ahead 
Permutation::IndexBackedPermutation  
Individual  Individual class  inherits a vector of Genotype objects 
Logger::Log  
Logger  Logging class  handles screen output and file logging 
MAT  
Tree::Primitives::MaxT< T >  Max function primitive (Tree genotype) 
Migration  Migration class  handles individual migration between demes 
Tree::Primitives::MinT< T >  Min function primitive (Tree genotype) 
Mod  
MOFitness  
MoveAhead  GP terminal, moves the ant one square ahead 
cart::Mul< T >  
Tree::Primitives::MulT< T >  Mul function primitive (Tree genotype) 
Mutation  Mutation class  handles mutation of _individuals_ (as opposed to MutationOp class that mutates genotypes) 
MutationOp  MutationOp base class 
MutationRate  
Tree::my_type  
MyAlg  
BitString::MyBitString  
MyFloatingPoint  
Tree::MyFunc  
Tree::MyTerminal  
Tree::Primitives::NegT< T >  Neg function primitive (Tree genotype) 
NeuralNetwork  
NNFloatingPoint  
Tree::Node  Node base class (Tree genotype) 
Not  
cart::Not< T >  
OneMaxEvalOp  OneMax problem evaluation class 
Operator  Abstract operator class 
OptIA  Optimization Immune Algorithm (optIA, see e.g. http://www.artificialimmunesystems.org/algorithms.shtml).This optIA implements:
 static cloning: all antibodies are cloned dup times, making the size of the clone population equal dup * poplationSize
 inversely proportional hypermutation: better antibodies are mutated less
 static pure aging  if an antibody exceeds tauB number of trials, it is replaced with a new randomly created antibody
 birthPhase: if the number of antibodies that survive the aging Phase is less than populationSize, new randomly created abs are added to the population
 optional elitism

Or  
cart::Or< T >  
ParallelAlgorithm  Parallel algorithm base class.All parallel algorithms should inherit this one 
ECF::Param  ECF parameter structure, as stored in the Registry 
ParticleSwarmOptimization  Particle swarm optimization algorithm (see e.g. http://en.wikipedia.org/wiki/Particle_swarm_optimization)PSO algorithm accepts only a single FloatingPoint genotype (vector of real values). Additionally, it adds the following genotypes for algorithm implementation:
 FloatingPoint genotype as particle velocity
 FloatingPoint genotype as bestsofar position
 FloatingPoint genotype as bestsofar fitness value

Permutation::Permutation  Permutation class  implements genotype as a vector of indices (permutation of indices) 
Permutation::PermutationCrsCOSA  Permutation genotype: COSA crossover operator (adapted from HeuristicLab) 
Permutation::PermutationCrsCyclic  Permutation genotype: Cyclic crossover operator (see e.g. http://www.rubicite.com/Tutorials/GeneticAlgorithms/CrossoverOperators/CycleCrossoverOperator.aspx) 
Permutation::PermutationCrsCyclic2  Permutation genotype: Cyclic version 2 crossover operator (adapted from HeuristicLab) 
Permutation::PermutationCrsDPX  Permutation genotype: DPX crossover operator (see e.g. itc.ktu.lt/itc342/Misev342.pdf) 
Permutation::PermutationCrsOBX  Permutation genotype: Order based crossover operator (see e.g. http://dx.doi.org/10.1016/j.amc.2007.10.013) 
Permutation::PermutationCrsOPX  Permutation genotype: OPX crossover operator (see e.g. itc.ktu.lt/itc342/Misev342.pdf) 
Permutation::PermutationCrsOX  Permutation genotype: OX crossover operator (see e.g. http://dx.doi.org/10.1016/j.amc.2007.10.013) 
Permutation::PermutationCrsOX2  Permutation genotype: Order crossover operator variant where algorithm starts from the beginning when copying the values from second parent (adapted from HeuristicLab) 
Permutation::PermutationCrsPBX  Permutation genotype: PBX crossover operator (see e.g. http://dx.doi.org/10.1016/j.amc.2007.10.013) 
Permutation::PermutationCrsPMX  Permutation genotype: PMX crossover operator (see e.g. http://dx.doi.org/10.1016/j.amc.2007.10.013) 
Permutation::PermutationCrsSPX  Permutation genotype: SPX crossover operator (see e.g. itc.ktu.lt/itc342/Misev342.pdf) 
Permutation::PermutationCrsULX  Permutation genotype: Uniform like crossover operator (see e.g. itc.ktu.lt/itc342/Misev342.pdf) 
Permutation::PermutationCrsUPMX  Permutation genotype: UMPX crossover operator (see e.g. itc.ktu.lt/itc342/Misev342.pdf) 
Permutation::PermutationMutIns  Permutation genotype: insert mutation operator (see e.g. http://dx.doi.org/10.1016/j.amc.2007.10.013) 
Permutation::PermutationMutInv  Permutation genotype: inversion mutation operator (see e.g. http://dx.doi.org/10.1016/j.amc.2007.10.013) 
Permutation::PermutationMutToggle  Permutation genotype: toggle mutation operator (see e.g. http://dx.doi.org/10.1016/j.amc.2007.10.013) 
Population  Population class  inherits a vector of Deme objects 
Tree::Primitives::PosT< T >  Pos function primitive (Tree genotype) 
PrimeEvalOp  
Tree::Primitives::Primitive  Base primitive class (Tree genotype) 
Tree::PrimitiveSet  Primitive set class: collects all Tree Primitives 
Prog2  GP function, executes 2 subtrees in sequence 
Prog3  GP function, executes 3 subtrees in sequence 
Randomizer  Abstract Randomizer class 
RandomSearch  Random search algorithmThe algorithm flow: 
RealValueGenotype  RealValueGenotype class  abstract genotype class for genotypes that represent a vector of real values (Binary, FloatingPoint) 
Registry  Repository for all the system parameters 
RouletteWheel  Generational algorithm with roulette wheel selection operatorThis algorithm is genotype independent (it can be used with any Genotype) 
Seed  
SelBestOp  Best individual selection operator 
SelectionOperator  Selection operator base class 
SelFitnessProportionalOp  Fitness proportional (and inverse proportional) individual selection operator 
SelRandomOp  Random individual selection operator 
SelWorstOp  Worst individual selection operator 
SimpleRandomizer  A simple randomizer that uses inbuilt random number generator 
cart::Sin< T >  
Tree::Primitives::Sin  Sin function primitive (Tree genotype) 
Sqrt  
StatCalc  Statistics calculation class 
State  State class  backbone of the framework 
SteadyStateTournament  Steady state algorithm with tournament elimination operatorThis algorithm is genotype independent (it can be used with any Genotype) 
cart::Sub< T >  
Tree::Primitives::SubT< T >  Sub function primitive (Tree genotype) 
SymbRegEvalOp  Symbolic regression evaluation operator 
TermFitnessValOp  Termination operator: terminates on a given fitness value 
Tree::Primitives::TerminalT< T >  Terminal tree node class (Tree genotype) 
TermMaxEvalOp  Termination operator: terminates on a given number of fitness evaluations 
TermMaxGenOp  Termination operator: terminates on a given number of generations 
TermMaxTimeOp  Termination operator: terminates on a given elapsed time 
TermStagnationOp  Termination operator: terminates when no improvement occurs in best individual for a given number of generations 
Tree::Tree  Tree class  implements genotype as a tree 
Tree::TreeCrxContextPreserved  Tree genotype: context presevation crx operator. Tries to make crossover at the 'same' point in both trees (with the same path from tree root node). Reference: http://dces.essex.ac.uk/staff/rpoli/gpfieldguide/53GPCrossover.html#11_3 
Tree::TreeCrxOnePoint  Tree genotype: one point crx operator. Tries to select a crossing point in parent tree's common region. Reference: http://dces.essex.ac.uk/staff/rpoli/gpfieldguide/53GPCrossover.html#11_3 
Tree::TreeCrxSimple  Tree genotype: simple tree crossover operator (with default 90% bias toward functional node) Reference: http://dces.essex.ac.uk/staff/rpoli/gpfieldguide/24RecombinationandMutation.html#7_4 
TreeCrxSimple  Tree genotype: simple tree crossover operator. Reference: http://dces.essex.ac.uk/staff/rpoli/gpfieldguide/24RecombinationandMutation.html#7_4 
Tree::TreeCrxSizeFair  Tree genotype: size fair crx operator. Reference: http://dces.essex.ac.uk/staff/rpoli/gpfieldguide/53GPCrossover.html#11_3 
Tree::TreeCrxUniform  Tree genotype: uniform crx operator. Reference: http://dces.essex.ac.uk/staff/rpoli/gpfieldguide/53GPCrossover.html#11_3 
Tree::TreeMutGauss  Tree genotype: standard normal distribution noise mutation operator. Applicable only on ephemereal random constants (ERC) of type 'double' 
Tree::TreeMutHoist  Tree genotype: mutation operator that replaces original tree with a randomly chosen subtree from the original tree 
Tree::TreeMutNodeComplement  Tree genotype: complement node mutation operator. For the operator to succeed, the chosen primitive must have a defined complement 
Tree::TreeMutNodeReplace  Tree genotype: node replacement mutation operator. Tries to replace the selected primitive with a different one with the same number of arguments 
Tree::TreeMutPermutation  Tree genotype: permutation mutation operator 
Tree::TreeMutShrink  Tree genotype: mutation operator that shrinks randomly chosen subtree 
Tree::TreeMutSubtree  Tree genotype: subtree sizefair mutation operator. This is a 'standard' GP subtree mutation 
TSPEvalOp  TSP evaluation operator 
TurnLeft  GP terminal, turns the ant left 
TurnRight  GP terminal, turns the ant right 
WriteTT  
XCS  XCS classifier system 
XCSParams  Parameters for the XCS algorithm 
XNor  
cart::Xnor< T >  
cart::Xor< T >  
Xor  