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Genetic Operators. Reproduction Crossover Mutation Permutation Editing Encapsulation Decimation Inversion Hoist Create Compress Expand. Reproduction. A parent is chosen from the population (using one of the selection methods). The individual is copied into the next generation.

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genetic operators
Genetic Operators
  • Reproduction
  • Crossover
  • Mutation
  • Permutation
  • Editing
  • Encapsulation
  • Decimation
  • Inversion
  • Hoist
  • Create
  • Compress
  • Expand
reproduction
Reproduction
  • A parent is chosen from the population (using one of the selection methods).
  • The individual is copied into the next generation.
  • The fitness of the individual does not have to be calculated.
crossover
Crossover
  • Two parents are selected from the population.
  • A crossover point is selected in each individual randomly.
  • The subtrees rooted at the crossover points are swapped.
  • In some cases the crossover operator can be reduced to mutation or reproduction.
  • A limit is usually set on the offspring size.
  • Variations of crossover
crossover example
Crossover Example

Crossover Fragments

mutation
Mutation
  • A parent is selected from the population.
  • A mutation point is selected at random.
  • The subtree rooted at this point is removed and replaced with a newly created subtree (could be a terminal).
  • Variations of mutation.
  • Can be reduced to reproduction.
  • Is used to maintain genetic diversity.
permutation
Permutation
  • A parent is chosen from the population.
  • A function node is randomly selected.
  • A permutation of the function arguments is randomly selected.
  • If the arity of the function node is two, the arguments are merely swapped.
editing
Editing
  • Is used to remove redundant code.
  • A parent is selected.
  • Examples
    • (+ 1 2 ) will be replaced by 3
    • (/ x 1) will be replaced with x
    • (AND T T) will be replaced with T
  • GP Parameters
    • A frequency parameter

Effect on Diversity

encapsulation
Encapsulation
  • Selection a parent.
  • Select a function node at random.
  • Remove the subtree rooted at this node.
  • This subtree forms the a new function and is given a label, e.g. E0, E1, etc.
  • The new function is added to the terminal set as it does not have arguments.
decimation
Decimation
  • Is to prevent loss of genetic diversity.
  • A percentage of the population is deleted during the specified generations.
  • Usually starts with a larger population.
  • GP parameters
    • Application rate
    • Frequency Rate
the inversion operator
The Inversion Operator
  • Select a parent.
  • Select two subtrees randomly.
  • Swap the subtrees.
  • Subtrees to be swapped must not be contained in each other
hoist
Hoist
  • Select a parent.
  • Randomly select a subtree within a the parent.
  • Copy the subtree into the next generation.
  • Example:
create
Create
  • A new tree is created using initial population generation and added to the next generation.
  • Maintain genetic diversity.
compress
Compress
  • Select a parent.
  • Select a subtree.
  • The part of the subtree up until a certain depth is defined as a new function.
  • The nodes below the level of the cut-off depth are considered as arguments to the module.
  • The module is named and added to the function set.
  • GP Parameters
    • Cut-off depth
compress example
Compress: Example

Cut-off Depth = 1

Arity=2

expand
Expand
  • Select a parent that contains a function node created by the compression operator.
  • Replace the function node with its corresponding subtree.