| 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| AlgAEliGpea2 | Asynchronous elimination global parallel algorithm (outdated version) |
| Algorithm | Algorithm base class |
| AlgSGenGpea | Synchronous generational global parallel algorithm |
| cart::And< T > | |
| 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)
|
| 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 on-line |
| 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 on-line |
| 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 (bit-flip) mutation operator |
| 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 |
| BitString::BitStringMutMix | BitString genotype mixing mutation operator |
| BitString::BitStringMutSimple | BitString genotype simple (one bit) mutation operator |
| 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 (1-d)*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 |
| cart::Cos< T > | |
| Tree::Primitives::Cos | Cos function primitive (Tree genotype) |
| Crossover | Crossover class - handles crossover of _individuals_ (as opposed to CrossoverOp class that crosses genotypes) |
| CrossoverOp | CrossoverOp base class |
| 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 > | |
| Tree::Primitives::DivT< T > | Div function primitive (Tree genotype) |
| Elimination | Elimination (generation gap) algorithm with roulette wheel elimination selection operatorThe algorithm flow: |
| 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) |
| EvaluateOp | Evaluation base class |
| EvolutionContext | Evolutionary context class |
| 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/IJIS-2003-18-3-309-338.PDF) |
| FloatingPoint::FloatingPointCrsBlx | FloatingPoint genotype: value on allele i is random value taken from min-max 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 alpha-beta 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 min-max 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/architecture-and-design/184409333?pgno=10) Currently implemented only for minimization problems! |
| GenHookeJeeves | New algorithm, in development |
| Genotype | Genotype base class |
| HallOfFame | Records a set of best-so-far individuals |
| IfFoodAhead | GP function, checks if the food is ahead |
| Permutation::IndexBackedPermutation | |
| Individual | Individual class - inherits a vector of Genotype objects |
| lastEvalStruct | |
| Logger::Log | |
| Logger | Logging class - handles screen output and file logging |
| 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) |
| 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 |
| Tree::my_type | |
| Tree::MyFunc | |
| Tree::MyTerminal | |
| Tree::Primitives::NegT< T > | Neg function primitive (Tree genotype) |
| Tree::Node | Node base class (Tree genotype) |
| cart::Not< T > | |
| OneMaxEvalOp | OneMax problem evaluation class |
| Operator | Abstract operator class |
| OptIA | Optimization Immune Algorithm (opt-IA, see e.g. http://www.artificial-immune-systems.org/algorithms.shtml).This opt-IA 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
|
| 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 |
| paramStruct | |
| 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 best-so-far position
- FloatingPoint genotype as best-so-far 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 (adapted from HeuristicLab) |
| Permutation::PermutationCrsCyclic2 | Permutation genotype: Cyclic version 2 crossover operator (adapted from HeuristicLab) |
| Permutation::PermutationCrsDPX | Permutation genotype: DPX crossover operator (see e.g. ?) |
| Permutation::PermutationCrsOBX | Permutation genotype: Order based crossover operator (adapted from HeuristicLab) |
| Permutation::PermutationCrsOPX | Permutation genotype: OPX crossover operator (see e.g. ?) |
| 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. ?) |
| Permutation::PermutationCrsULX | Permutation genotype: Uniform like crossover operator (adapted from HeuristicLab) |
| Permutation::PermutationCrsUPMX | Permutation genotype: UMPX crossover operator (see e.g. ?) |
| 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) |
| 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 operatorThe algorithm flow: |
| 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 in-built random number generator |
| Tree::Primitives::Sin | Sin function primitive (Tree genotype) |
| cart::Sin< T > | |
| StatCalc | Statistics calculation class |
| State | State class - backbone of the framework |
| SteadyStateTournament | Steady state algorithm with tournament elimination operatorThe algorithm flow: |
| 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/gp-field-guide/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/gp-field-guide/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/gp-field-guide/24RecombinationandMutation.html#7_4 |
| TreeCrxSimple | Tree genotype: simple tree crossover operator. Reference: http://dces.essex.ac.uk/staff/rpoli/gp-field-guide/24RecombinationandMutation.html#7_4 |
| Tree::TreeCrxSizeFair | Tree genotype: size fair crx operator. Reference: http://dces.essex.ac.uk/staff/rpoli/gp-field-guide/53GPCrossover.html#11_3 |
| Tree::TreeCrxUniform | Tree genotype: uniform crx operator. Reference: http://dces.essex.ac.uk/staff/rpoli/gp-field-guide/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 size-fair 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 |
| twoDoubles | |
| createfolders::Usage | |
| XCS | XCS classifier system |
| XCSParams | Parameters for the XCS algorithm |
| cart::Xnor< T > | |
| cart::Xor< T > | |
