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Hierarchical policy decomposition

Definition

Hierarchical policy decomposition is the principle of splitting a complex decision system into two or more layers operating at different time horizons and abstraction levels: a slow/strategic layer that sets long-term goals and constraints, and a fast/tactical layer that makes immediate decisions within those bounds.

The pattern appears across domains: - Robotics / autonomous driving: slower planning layer (goals, constraints, long horizons) + faster control loops (steering, braking) - LLM agents: deliberate planning + rapid step-by-step tool use - Notification systems: weekly frequency planning + per-opportunity message selection

The key insight is that decoupling time horizons prevents short-term optimization from undermining long-term objectives — e.g., maximizing today's click-through without accounting for cumulative fatigue.

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