culebra.trainer.ea module

Implementation of some evolutionary trainers.

This module provides some popular evolutionary algorithms:

  • The EA class, which implements the simplest EA

  • The ElitistEA class, which provides an elitist EA

  • The NSGA class, which implements a multi-objective EA, based on Non-dominated sorting, able to run both the NSGA-II and the NSGA-III algorithms

Attributes

DEFAULT_CROSSOVER_PROB = 0.8

Default crossover probability.

DEFAULT_ELITE_SIZE = 5

Default number of elite individuals.

DEFAULT_GENE_IND_MUTATION_PROB = 0.1

Default gene independent mutation probability.

DEFAULT_MUTATION_PROB = 0.2

Default mutation probability.

DEFAULT_NSGA_SELECTION_FUNC = <function :func:`deap.tools.selection.selNSGA2`>

Default selection function for NSGA-based algorithms.

DEFAULT_NSGA3_REFERENCE_POINTS_P = 4

Default number of divisions along each objective for the reference points of NSGA-III.

DEFAULT_POP_SIZE = 100

Default population size.

DEFAULT_SELECTION_FUNC = :func:`functools.partial`(<function :func:`deap.tools.selection.selTournament`>, tournsize=2)

Default selection function.