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Tree-based genetic programming

Figure 8.6 In tree-based genetic programming, individuals are represented as trees. A sample individual is shown on the left. This individual represents a symbolic expression that evaluates to 2x — 1. [Pg.200]

MOGP is based on the more traditional optimisation method genetic programming (GP), which is a type of GA [53,54]. The main difference between GP and a GA is in the chromosome representation in a GA an individual is usually represented by a fixed-length linear string, whereas in GP individuals are represented by treelike structures hence, they can vary in shape and size as the population undergoes evolution. The internal nodes of the tree, typically represent mathematical operators, and the terminal nodes, typically represent variables and constant values thus, the chromosome can represent a mathematical expression as shown in Fig. 4. [Pg.146]


See other pages where Tree-based genetic programming is mentioned: [Pg.199]    [Pg.199]    [Pg.394]    [Pg.276]    [Pg.137]    [Pg.368]    [Pg.596]    [Pg.341]    [Pg.1142]    [Pg.85]    [Pg.111]    [Pg.111]    [Pg.199]    [Pg.223]    [Pg.6]   
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Genetic programming

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