/**
 * SMI-1535: Preference Learner Integration Tests
 *
 * Tests the IPreferenceLearner interface for updating user profiles
 * based on interaction signals in the Recommendation Learning Loop.
 *
 * Test Cases:
 * 1. Update profile from single ACCEPT signal
 * 2. Update profile from single DISMISS signal
 * 3. Batch update with 100 signals
 * 4. Weight decay after 30 days
 * 5. Weight bounds enforcement (-2.0 to 2.0)
 * 6. Category weight accumulation
 * 7. Trust tier preference learning
 * 8. Author preference learning
 * 9. Cold start default weights
 * 10. Profile persistence across sessions
 *
 * @see packages/core/src/learning/interfaces.ts
 * @see docs/internal/execution/phase5-testing-execution.md
 */
export {};
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