evolutionRestartConditions: Evolution restart conditions
In rgp: R genetic programming framework

Description Usage Arguments Details

Evolution restart conditions are predicates (functions that return a single logical value) of the signature function(population, fitnessFunction, stepNumber, evaluationNumber, bestFitness, timeElapsed). They are used to decide when to restart a GP evolution run that might be stuck in a local optimum. Evolution restart conditions are objects of the same type and class as evolution stop conditions. They may be freely substituted for each other.

makeEmptyRestartCondition()

makeStepLimitRestartCondition(stepLimit = 10)

makeFitnessStagnationRestartCondition(fitnessHistorySize = 100,
  testFrequency = 10, fitnessStandardDeviationLimit = 1e-06)

makeFitnessDistributionRestartCondition(testFrequency = 100,
  fitnessStandardDeviationLimit = 1e-06)

`stepLimit`	The step limit for `makeStepLimitRestartCondition`.
`fitnessHistorySize`	The number of past best fitness values to look at when calculating the best fitness standard deviation for `makeFitnessStagnationRestartCondition`.
`testFrequency`	The frequency to test for the restart condition, in evolution steps. This parameter is mainly used with restart condititions that are expensive to calculate.
`fitnessStandardDeviationLimit`	The best fitness standard deviation limit for `makeFitnessStagnationRestartCondition`.

makeEmptyRestartCondition creates a restart condition that is never fulfilled, i.e. restarts will never occur. makeStepLimitRestartCondition creates a restart condition that holds if the number if evolution steps is an integer multiple of a given step limit. restarts will never occur. makeFitnessStagnationRestartCondition creates a restart strategy that holds if the standard deviation of a last fitnessHistorySize best fitness values falls below a given fitnessStandardDeviationLimit. makeFitnessDistributionRestartCondition creates a restart strategy that holds if the standard deviation of the fitness values of the individuals in the current population falls below a given fitnessStandardDeviationLimit.