Package | Description |
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org.processmining.plugins.etm.engines | |
org.uncommonseditedbyjoosbuijs.watchmaker.framework |
This package provides a framework for evolutionary computation.
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org.uncommonseditedbyjoosbuijs.watchmaker.framework.interactive |
Classes for implementing interactive evolutionary algorithms.
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org.uncommonseditedbyjoosbuijs.watchmaker.framework.islands |
An implementation of island model evolution.
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org.uncommonseditedbyjoosbuijs.watchmaker.framework.selection |
Various selection strategies for use with evolutionary algorithms.
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Modifier and Type | Method and Description |
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protected java.util.List<EvaluatedCandidate<NAryTree>> |
LoggingEvolutionEngine.evaluatePopulation(java.util.List<NAryTree> population) |
java.util.List<EvaluatedCandidate<NAryTree>> |
LoggingEvolutionEngine.evolvePopulation() |
java.util.List<EvaluatedCandidate<NAryTree>> |
ParetoEngine.evolvePopulation(int populationSize,
int eliteCount,
java.util.Collection<NAryTree> seedCandidates,
TerminationCondition... conditions)
Execute the evolutionary algorithm until one of the termination conditions is met,
then return all of the candidates from the final generation.
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protected java.util.List<EvaluatedCandidate<NAryTree>> |
ParetoEngine.nextEvolutionStep(java.util.List<EvaluatedCandidate<NAryTree>> evaluatedPopulation,
int eliteCount,
java.util.Random rng) |
protected java.util.List<EvaluatedCandidate<NAryTree>> |
TreeEvolutionEngine.nextEvolutionStep(java.util.List<EvaluatedCandidate<NAryTree>> evaluatedPopulation,
int eliteCount,
java.util.Random rng)
This method performs a single step/iteration of the evolutionary process.
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Modifier and Type | Method and Description |
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void |
LoggingEvolutionEngine.logPopulation(java.util.List<EvaluatedCandidate<NAryTree>> result) |
abstract java.lang.String |
LoggingEvolutionEngine.logResult(java.util.List<EvaluatedCandidate<NAryTree>> result)
Write the current result to a file, should be implemented by each
specific engine
|
java.lang.String |
ParetoEngine.logResult(java.util.List<EvaluatedCandidate<NAryTree>> result) |
java.lang.String |
TreeEvolutionEngine.logResult(java.util.List<EvaluatedCandidate<NAryTree>> result)
Builds a string that described the whole provided result such that it can
be logged
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protected java.util.List<EvaluatedCandidate<NAryTree>> |
ParetoEngine.nextEvolutionStep(java.util.List<EvaluatedCandidate<NAryTree>> evaluatedPopulation,
int eliteCount,
java.util.Random rng) |
protected java.util.List<EvaluatedCandidate<NAryTree>> |
TreeEvolutionEngine.nextEvolutionStep(java.util.List<EvaluatedCandidate<NAryTree>> evaluatedPopulation,
int eliteCount,
java.util.Random rng)
This method performs a single step/iteration of the evolutionary process.
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Modifier and Type | Method and Description |
---|---|
protected java.util.List<EvaluatedCandidate<T>> |
AbstractEvolutionEngine.evaluatePopulation(java.util.List<T> population)
Takes a population, assigns a fitness score to each member and returns
the members with their scores attached, sorted in descending order of
fitness (descending order of fitness score for natural scores, ascending
order of scores for non-natural scores).
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java.util.List<EvaluatedCandidate<T>> |
AbstractEvolutionEngine.evolvePopulation(int populationSize,
int eliteCount,
java.util.Collection<T> seedCandidates,
TerminationCondition... conditions)
Execute the evolutionary algorithm until one of the termination conditions is met,
then return all of the candidates from the final generation.
|
java.util.List<EvaluatedCandidate<T>> |
EvolutionEngine.evolvePopulation(int populationSize,
int eliteCount,
java.util.Collection<T> seedCandidates,
TerminationCondition... conditions)
Execute the evolutionary algorithm until one of the termination conditions is met,
then return all of the candidates from the final generation.
|
java.util.List<EvaluatedCandidate<T>> |
AbstractEvolutionEngine.evolvePopulation(int populationSize,
int eliteCount,
TerminationCondition... conditions)
Execute the evolutionary algorithm until one of the termination conditions is met,
then return all of the candidates from the final generation.
|
java.util.List<EvaluatedCandidate<T>> |
EvolutionEngine.evolvePopulation(int populationSize,
int eliteCount,
TerminationCondition... conditions)
Execute the evolutionary algorithm until one of the termination conditions is met,
then return all of the candidates from the final generation.
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protected abstract java.util.List<EvaluatedCandidate<T>> |
AbstractEvolutionEngine.nextEvolutionStep(java.util.List<EvaluatedCandidate<T>> evaluatedPopulation,
int eliteCount,
java.util.Random rng)
This method performs a single step/iteration of the evolutionary process.
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protected java.util.List<EvaluatedCandidate<T>> |
EvolutionStrategyEngine.nextEvolutionStep(java.util.List<EvaluatedCandidate<T>> evaluatedPopulation,
int eliteCount,
java.util.Random rng)
This method performs a single step/iteration of the evolutionary process.
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protected java.util.List<EvaluatedCandidate<T>> |
GenerationalEvolutionEngine.nextEvolutionStep(java.util.List<EvaluatedCandidate<T>> evaluatedPopulation,
int eliteCount,
java.util.Random rng)
This method performs a single step/iteration of the evolutionary process.
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protected java.util.List<EvaluatedCandidate<T>> |
SteadyStateEvolutionEngine.nextEvolutionStep(java.util.List<EvaluatedCandidate<T>> evaluatedPopulation,
int eliteCount,
java.util.Random rng)
This method performs a single step/iteration of the evolutionary process.
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<T extends java.lang.Comparable<? super T>> |
FitnessEvaluationWorker.submit(org.uncommonseditedbyjoosbuijs.watchmaker.framework.FitnessEvalutationTask<T> task) |
Modifier and Type | Method and Description |
---|---|
int |
EvaluatedCandidate.compareTo(EvaluatedCandidate<T> evaluatedCandidate)
Compares this candidate's fitness score with that of the specified
candidate.
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Modifier and Type | Method and Description |
---|---|
protected void |
SteadyStateEvolutionEngine.doReplacement(java.util.List<EvaluatedCandidate<T>> existingPopulation,
java.util.List<EvaluatedCandidate<T>> newCandidates,
int eliteCount,
java.util.Random rng)
Add the offspring to the population, removing the same number of existing
individuals to make space for them.
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protected void |
SteadyStateEvolutionEngine.doReplacement(java.util.List<EvaluatedCandidate<T>> existingPopulation,
java.util.List<EvaluatedCandidate<T>> newCandidates,
int eliteCount,
java.util.Random rng)
Add the offspring to the population, removing the same number of existing
individuals to make space for them.
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static <T> PopulationData<T> |
EvolutionUtils.getPopulationData(java.util.List<EvaluatedCandidate<T>> evaluatedPopulation,
boolean naturalFitness,
int eliteCount,
int iterationNumber,
long startTime)
Gets data about the current population, including the fittest candidate
and statistics about the population as a whole.
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protected abstract java.util.List<EvaluatedCandidate<T>> |
AbstractEvolutionEngine.nextEvolutionStep(java.util.List<EvaluatedCandidate<T>> evaluatedPopulation,
int eliteCount,
java.util.Random rng)
This method performs a single step/iteration of the evolutionary process.
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protected java.util.List<EvaluatedCandidate<T>> |
EvolutionStrategyEngine.nextEvolutionStep(java.util.List<EvaluatedCandidate<T>> evaluatedPopulation,
int eliteCount,
java.util.Random rng)
This method performs a single step/iteration of the evolutionary process.
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protected java.util.List<EvaluatedCandidate<T>> |
GenerationalEvolutionEngine.nextEvolutionStep(java.util.List<EvaluatedCandidate<T>> evaluatedPopulation,
int eliteCount,
java.util.Random rng)
This method performs a single step/iteration of the evolutionary process.
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protected java.util.List<EvaluatedCandidate<T>> |
SteadyStateEvolutionEngine.nextEvolutionStep(java.util.List<EvaluatedCandidate<T>> evaluatedPopulation,
int eliteCount,
java.util.Random rng)
This method performs a single step/iteration of the evolutionary process.
|
<S extends T> |
SelectionStrategy.select(java.util.List<EvaluatedCandidate<S>> population,
boolean naturalFitnessScores,
int selectionSize,
java.util.Random rng)
Select the specified number of candidates from the population.
|
static <T> void |
EvolutionUtils.sortEvaluatedPopulation(java.util.List<EvaluatedCandidate<T>> evaluatedPopulation,
boolean naturalFitness)
Sorts an evaluated population in descending order of fitness
(descending order of fitness score for natural scores, ascending
order of scores for non-natural scores).
|
Modifier and Type | Method and Description |
---|---|
<S extends T> |
InteractiveSelection.select(java.util.List<EvaluatedCandidate<S>> population,
boolean naturalFitnessScores,
int selectionSize,
java.util.Random rng)
Select the specified number of candidates from the population.
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Modifier and Type | Method and Description |
---|---|
<T> void |
Migration.migrate(java.util.List<java.util.List<EvaluatedCandidate<T>>> islandPopulations,
int migrantCount,
java.util.Random rng) |
<T> void |
RingMigration.migrate(java.util.List<java.util.List<EvaluatedCandidate<T>>> islandPopulations,
int migrantCount,
java.util.Random rng)
Migrates a fixed number of individuals from each island to the adjacent island.
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Modifier and Type | Method and Description |
---|---|
<S> java.util.List<S> |
RankSelection.select(java.util.List<EvaluatedCandidate<S>> population,
boolean naturalFitnessScores,
int selectionSize,
java.util.Random rng)
Select the specified number of candidates from the population.
|
<S> java.util.List<S> |
RouletteWheelSelection.select(java.util.List<EvaluatedCandidate<S>> population,
boolean naturalFitnessScores,
int selectionSize,
java.util.Random rng)
Selects the required number of candidates from the population with
the probability of selecting any particular candidate being proportional
to that candidate's fitness score.
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<S> java.util.List<S> |
SigmaScaling.select(java.util.List<EvaluatedCandidate<S>> population,
boolean naturalFitnessScores,
int selectionSize,
java.util.Random rng)
Select the specified number of candidates from the population.
|
<S> java.util.List<S> |
StochasticUniversalSampling.select(java.util.List<EvaluatedCandidate<S>> population,
boolean naturalFitnessScores,
int selectionSize,
java.util.Random rng) |
<S> java.util.List<S> |
TournamentSelection.select(java.util.List<EvaluatedCandidate<S>> population,
boolean naturalFitnessScores,
int selectionSize,
java.util.Random rng) |
<S> java.util.List<S> |
TruncationSelection.select(java.util.List<EvaluatedCandidate<S>> population,
boolean naturalFitnessScores,
int selectionSize,
java.util.Random rng)
Selects the fittest candidates.
|