Interaction inside Evolution Sample Clauses

Interaction inside Evolution. An Evolutionary Algorithm could also be viewed as an iterative process of interacting individuals. Generating offspring is often done using multiple individuals and combining their traits is an interaction for instance, while selection could be viewed as one big interaction between all the individuals that results in finding the fittest one. The benefit of looking at evolution as having interaction between individuals in a population is that some hard to understand phenomena observed in EA become understandable. A good example of a non trivial interaction inside an Evolutionary Algo- rithm is self-adaptation. With self-adaptation some parameters for the EA that are normally fixed or are changing using some mathematical function, now change using the evolution itself. For instance the parameters with which an individual is mutated (mutation amount / speed) can be part of the individual’s description. The idea being that when a certain way of mutating an individual is more appropriate at a certain stage of the evo- lution, the offspring generated using that mutation will on average have a better fitness. Which means that selection will probably select individuals with better mutation settings which then propagate towards the offspring of these individuals and so on. This works for mutation parameters, but also for more complicated global parameters like selection and offspring gener- ation. In all cases the algorithm becomes more flexible and can handle a lot more different problems using the same settings, but some unwanted behavior resulting from using this approach is harder to understand and fix.
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