1. What is Hierarchical Planning?
In traditional planning (like STRIPS), a planner works directly with primitive actions.
In hierarchical planning, we start with high-level abstract tasks and decompose them step-by-step into simpler tasks.
2. Key Concepts
| Term | Meaning |
|---|---|
| Task | Any activity that needs to be accomplished |
| Primitive Task | A task that can be executed directly (like move(robot, A, B)) |
| Compound Task | A higher-level task that needs to be broken into subtasks (like buildHouse) |
| Task Network | A set of tasks with temporal or ordering constraints |
| Decomposition | Process of refining a compound task into subtasks |
| Methods | Rules that specify how to decompose compound tasks |
3. How It Works
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Start with a high-level goal
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Select a method to decompose that goal
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Decompose compound tasks into smaller subtasks (recursively)
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Repeat until only primitive tasks remain
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Execute the primitive actions in a valid order
4. Example: Building a House 🏠
High-Level Task:
BuildHouse
Method:
BuildHouse → [GetPermit, HireContractor, Construct, PayContractor]
Further Decomposition:
Construct → [LayFoundation, BuildWalls, InstallRoof]
Eventually:
InstallRoof → [OrderMaterials, HireRoofers, SuperviseInstallation]
These leaf-level tasks will eventually map to executable actions like:
Order(Materials, SupplierX), Pay(Contractor, Amount)
5. Benefits of Hierarchical Planning
Scalability: Reduces complexity by breaking large problems into manageable parts
Reusability: Methods can be reused for similar tasks
Abstraction: Focus on high-level strategy rather than low-level mechanics
Human-Like Reasoning: Mimics how humans naturally plan complex tasks
6. Applications
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Robotics: e.g., plan to clean a house → clean rooms → sweep floor, etc.
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Game AI: NPC behaviors like “attack base” → move to location → fire weapon
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Logistics: Transporting goods → load → travel → unload
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Workflow Management: Business processes → customer onboarding → send welcome email, etc.
7. Challenges
Choosing the Right Decomposition: Multiple methods may apply; selecting the optimal one is non-trivial
Execution Monitoring: Real-world tasks may fail; planner must adapt
Complex Constraints: Handling preconditions and interactions between subtasks is difficult
Summary Table
| Feature | Hierarchical Planning |
|---|---|
| Task Type | Compound and primitive |
| Core Mechanism | Task decomposition |
| Knowledge Used | Domain-specific methods |
| Planning Granularity | High-level to low-level |
| Analogy | Project breakdown into subtasks |
| Strength | Efficient for complex domains |
Hierarchical Planning offers a structured and efficient approach for solving real-world planning problems by “thinking big, and refining down.” It blends symbolic planning with abstraction and is key to many modern AI systems.