Use Random Numerical Constants
Check this box if you want to use the GEP-RNC learning algorithm of APS. This algorithm has a facility for handling random numerical constants and it evolves models with them.

Constants per Gene
The number of random numerical constants associated with each gene.

Data Type
The data type (integer or floating-point) you think appropriate for the random numerical constants that will be used in the creation of your models. For Integer constants only integer values in the interval [-2147483648, 2147483647] are acceptable. For Floating-point constants a double-precision floating-point value with a range of -1.79769313486231E308 to -4.94065645841247E-324 for negative values, 4.94065645841247E-324 to 1.79769313486231E308 for positive values, and 0 are acceptable.

Lower Bound
Sets the lower bound of the interval from which random numerical constants are drawn.

Upper Bound
Sets the upper bound of the interval from which random numerical constants are drawn.

RNC Mutation
The RNC mutation rate used to create genetic variation in the arrays of random numerical constants. The default is 0.01.

Dc Mutation
The Dc mutation rate used to create genetic variation. The default is 0.044.

Dc Inversion
The Dc inversion rate used to create genetic variation. The default is 0.1.

Dc IS Transposition
The Dc IS transposition rate used to create genetic variation. The default is 0.1.

Defaults
Resets the rates of all the above genetic operators to the default values.