In artificial intelligence (AI) planning, which approach builds a plan using successive representations at multiple levels of detail, refining high-level actions into lower-level steps as needed?

Introduction / Context:
Planning in artificial intelligence (AI) is about deciding a sequence of actions that transform the world from an initial state to a desired goal state. Some approaches reason at a single level of detail, while others organize decisions into layers. The question asks for the planning style that explicitly uses several levels of description so that a high-level plan is progressively refined into concrete, executable steps.

Given Data / Assumptions:

• The plan is represented at multiple abstraction levels.
• Higher-level actions can be decomposed into lower-level subactions.
• The process is iterative: refine top goals into more detailed operations.

Concept / Approach:

Hierarchical planning (often called Hierarchical Task Network, or HTN, planning) models tasks at different granularities. A task such as ‘‘travel to city’’ can be decomposed into ‘‘book ticket,’’ ‘‘go to airport,’’ and ‘‘board flight,’’ which in turn decompose further. This layered organization lets planners reason efficiently, reuse methods, and delay low-level commitments until necessary.

Step-by-Step Solution:

Verification / Alternative check:

Classic AI planning literature describes HTN planners as operating via methods that refine compound tasks into primitive actions. This is precisely the idea of successive representations across levels of detail.

Why Other Options Are Wrong:

Project planning: Concerned with schedules and resources, not multi-level symbolic decomposition.

Non-hierarchical planning: Operates at a single granularity; no layered refinement.

All of the above / None of the above: Contradict the clear definition of hierarchical planning.

Common Pitfalls:

Confusing managerial project plans with AI plan representations; assuming any planner implicitly uses multiple levels (many do not).

Final Answer:

hierarchical planning