Package org.uncommons.watchmaker.framework.selection

Various selection strategies for use with evolutionary algorithms.

See:
Description

Class Summary

RankSelection	A selection strategy that is similar to fitness-proportionate selection except that is uses relative fitness rather than absolute fitness in order to determine the probability of selection for a given individual (i.e.
RouletteWheelSelection	Implements selection of n candidates from a population by selecting n candidates at random where the probability of each candidate getting selected is proportional to its fitness score.
SigmaScaling	An alternative to straightforward fitness-proportionate selection such as that offered by RouletteWheelSelection and StochasticUniversalSampling.
StochasticUniversalSampling	An alternative to RouletteWheelSelection as a fitness-proportionate selection strategy.
TournamentSelection	Selection strategy that picks a pair of candidates at random and then selects the fitter of the two candidates with probability p, where p is the configured selection probability (therefore the probability of the less fit candidate being selected is 1 - p).
TruncationSelection	Implements selection of n candidates from a population by simply selecting the n candidates with the highest fitness scores (the rest are discarded).

Package org.uncommons.watchmaker.framework.selection Description

Various selection strategies for use with evolutionary algorithms.

Author:

Daniel Dyer