CMA-ES
Covariance Matrix Adaptation Evolution Strategy.
CMAESAlgorithm configuration for Covariance Matrix Adaptation Evolution Strategy.
- class CMAESAlgorithm(log_info=False, evaluations=100000, max_evaluations_without_improvement=10000, max_time_without_improvement=300, min_improvement=1e-06, max_restart_count=0, prng_seed=None, time_limit=60, population_size=NUM_VARIABLES, consistency_check=False, cc=4 / NUM_VARIABLES, cs=2 / NUM_VARIABLES, damps=1 + 2 / NUM_VARIABLES, ccov=1 / NUM_VARIABLES, ccovsep=1 / NUM_VARIABLES * NUM_VARIABLES, sigma=0.5, diagonal_iterations=NUM_VARIABLES)[source]
Covariance Matrix Adaptation Evolution Strategy.
- population_size: int | NumericExpression | Parameter | Calculation = NUM_VARIABLES
Number of candidate solutions per generation.
- cc: float | NumericExpression | Parameter | Calculation = (4 / NUM_VARIABLES)
Covariance-matrix cumulation constant.
- cs: float | NumericExpression | Parameter | Calculation = (2 / NUM_VARIABLES)
Step-size cumulation constant.
- damps: float | NumericExpression | Parameter | Calculation = (1 + (2 / NUM_VARIABLES))
Damping factor for step-size control.
- ccov: float | NumericExpression | Parameter | Calculation = (1 / NUM_VARIABLES)
Learning rate for the covariance-matrix update.
- ccovsep: float | NumericExpression | Parameter | Calculation = (1 / (NUM_VARIABLES * NUM_VARIABLES))
Learning rate for the separable update.
- sigma: float | NumericExpression | Parameter | Calculation = 0.5
Initial step size.
- diagonal_iterations: int | NumericExpression | Parameter | Calculation = NUM_VARIABLES
Iterations using the diagonal-only update before the full update.