/**
 * Multi-Head Attention Mechanism Analysis for Latent Space Exploration
 *
 * Validates RuVector GNN's multi-head attention implementation against industry benchmarks:
 * - Pinterest PinSage: 150% hit-rate improvement
 * - Google Maps: 50% ETA accuracy boost
 * - PyTorch Geometric: Production-proven GAT implementations
 *
 * This simulation measures attention weight distribution, query enhancement quality,
 * and learning convergence rates to validate AgentDB's unique GNN integration.
 */
import type { SimulationScenario } from '../../types';
export interface AttentionMetrics {
    weightDistribution: {
        entropy: number;
        concentration: number;
        sparsity: number;
        headDiversity: number;
    };
    queryEnhancement: {
        cosineSimilarityGain: number;
        recallImprovement: number;
        ndcgImprovement: number;
    };
    learning: {
        convergenceEpochs: number;
        sampleEfficiency: number;
        transferability: number;
    };
    performance: {
        forwardPassMs: number;
        backwardPassMs: number;
        memoryMB: number;
    };
}
export interface MultiHeadAttentionConfig {
    heads: number;
    hiddenDim: number;
    layers: number;
    dropout: number;
    attentionType: 'gat' | 'transformer' | 'hybrid';
}
export declare const attentionAnalysisScenario: SimulationScenario;
export default attentionAnalysisScenario;
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