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Hyperparameter adaptation mechanisms
This module provides various approaches to hyperparameter control in evolutionary algorithms, following Eiben et al.’s classification:
- Deterministic Control (Schedules): Parameters change according to a predetermined schedule
- Adaptive Control: Parameters adapt based on feedback from the search process
- Self-Adaptive Control: Parameters are encoded in the genome and evolve
- Bayesian Learning: Parameters are inferred using probabilistic methods
Modules§
- adaptive
- Adaptive control mechanisms
- bayesian
- Bayesian hyperparameter learning
- prelude
- schedules
- Parameter schedules for deterministic control
- self_
adaptive - Self-adaptive control mechanisms