HSGEP-0.1.0: Gene Expression Programming evolutionary algorithm in HaskellSource codeContentsIndex
type FitnessFunction a b = a -> b -> Double -> Double -> Double
type ExpressionFunction a = Individual -> Genome -> a
type TestCase a = SymTable a
type TestDict a = [TestCase a]
type TestOuts = [Double]
gepDriver :: SimParams -> Rates -> Genome -> TestDict b -> TestOuts -> FitnessFunction a (TestCase b) -> ExpressionFunction a -> IO (Double, [String])
type FitnessFunction a b = a -> b -> Double -> Double -> DoubleSource
Fitness function type
type ExpressionFunction a = Individual -> Genome -> aSource
Function to express an individual into a list of ET structures
type TestCase a = SymTable aSource
A test case maps a list of terminals to float values
type TestDict a = [TestCase a]Source
A test dictionary is a set of test cases
type TestOuts = [Double]Source
The set of outputs expected for each entry in the test dictionary
:: SimParamsSimulation parameters
-> RatesRates for genetic operators
-> GenomeGenome that individuals are drawn from
-> TestDict bTest dictionary for fitness testing
-> TestOutsExpected test results for test dictionary
-> FitnessFunction a (TestCase b)Fitness testing function
-> ExpressionFunction aString to ET expression function
-> IO (Double, [String])Return best individual fitness and population
Generic driver to be called from specific GEP program instances in their main routine.
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