Struct MetaLearningOptimizer 

pub struct MetaLearningOptimizer {
    pub config: MetaLearningConfig,
    pub experience_db: Arc<RwLock<ExperienceDatabase>>,
    pub feature_extractor: Arc<Mutex<FeatureExtractor>>,
    pub meta_learner: Arc<Mutex<MetaLearner>>,
    pub nas_engine: Arc<Mutex<NeuralArchitectureSearch>>,
    pub portfolio_manager: Arc<Mutex<AlgorithmPortfolio>>,
    pub multi_objective_optimizer: Arc<Mutex<MultiObjectiveOptimizer>>,
    pub transfer_learner: Arc<Mutex<TransferLearner>>,
}

Main meta-learning optimization engine

Fields

config: MetaLearningConfig

Configuration

experience_db: Arc<RwLock<ExperienceDatabase>>

Experience database

feature_extractor: Arc<Mutex<FeatureExtractor>>

Feature extractor

meta_learner: Arc<Mutex<MetaLearner>>

Meta-learner

nas_engine: Arc<Mutex<NeuralArchitectureSearch>>

Neural architecture search engine

portfolio_manager: Arc<Mutex<AlgorithmPortfolio>>

Algorithm portfolio manager

multi_objective_optimizer: Arc<Mutex<MultiObjectiveOptimizer>>

Multi-objective optimizer

transfer_learner: Arc<Mutex<TransferLearner>>

Transfer learning system

Implementations

impl MetaLearningOptimizer

pub fn new(config: MetaLearningConfig) -> Self

pub fn recommend_strategy( &mut self, problem: &IsingModel, ) -> ApplicationResult<RecommendedStrategy>

Recommend optimization strategy for a given problem

pub fn record_experience( &mut self, experience: OptimizationExperience, ) -> ApplicationResult<()>

Record optimization experience for learning

pub fn get_statistics(&self) -> ApplicationResult<MetaLearningStatistics>

Get meta-learning statistics