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Evolutionary Learning
Explicit Components
Loop
Octopus
Supervised Learning
Utilities
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Mutate a solution's parameter values. It is recommended to work with parameters between 0 and 1. Although the mutation-algorithm can handle values outside this domain, the approach to scaling the mutation is experimental and not according to literature.

Inputs

NameIDDescriptionType
Octopus SolutionOSThe Octopus Solution to mutateOctopus Solution
Mutation ProbabilityPThe mutation probability defines how many parameters are changed in average.Number
Mutation RateRThe mutation rate defines to which extent the mutation changes a parameterNumber
SeedSSeed for random number generation as the basis for the mutationInteger

Outputs

NameIDDescriptionType
The mutated Octopus SolutionOSThe mutated Octopus SolutionOctopus Solution

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