Package jaga.experiment

Interface Summary

ConfigurableExperiment	Allows data to be fed in to this experiment after being constructed.
ConfigurableRandomInputExperiment	Used for experiments where the randomness of the input sequence can be controlled for example so taht every generation the same input sequence is used for all individuals but this is modified for the next generation.
Experiment	An Experiment is a purpose we wish the individuals to perform, such as being an AND gate, or surviving in a tank full of piranhas.
FitnessFunction	A fitness function must provide a fitness value given the inputs, outputs and desired outputs of an individual evaluation.
TestPatternGenerator	Used to plug-in to experiments so that their generateInput method can be configurable.

Class Summary

CompleteShuffledTPG	Will generate a test pattern with all 2^I input vectors (where I is the nr.
ConfigurableRandomInputMultiOutputExperiment	Multiple Output Experiments allow many experiments sharing inputs to be bundled into the same one.
CorrelationFitnessFunction	Given desired output samples and actual output samples will calculate fitness as the statistical correlation between them.
ExperimentLib	Provides common functionality used by many Experiment imlementations.
MultiOutputExperiment	Multiple Output Experiments allow many experiments sharing inputs to be bundled into the same one.
MultipleSampleAvgFitnessFunction	This Wrapper fitness function extracts multiple output samples from the actual output by averaging values at certain points.
NRepeatsTPG	This Pattern Generator generates random input vectors at each step until all possible 2^I (where I is the nr.
PerRowFitnessFunction	Creates a single output series whose value is 0 for rows where every output in Q is equal to those in desQ, and a 1 otherwise.
PessimisticFitnessFunction	If a test pattern of length TP is applied containing only V unique test vectors, then this fitness function (FF) wrapper will provide a test pattern of length V to its internal FF with a 1 where an output was equal to the desired at every application of the current test vector and a 0 if at any application of that vector it was different.
SimpleCorrelationFitnessFunction	A variant of the CorrelationFitnessFunction, it requires less computation.
SingleNoisySizeSampleAvgFitnessFunction	Similar to the SingleSampleAvgFitnessFunction but with a varying size window.
SingleSampleAvgFitnessFunction	A single sample at the end of each session while inputs are applied is used as the ouptput for that session, instead of using all inputSampleSeparation bits.
SumFitnessFunction	This fitness function calculates fitness as (correct bits/total bits) averaged over all outputs.