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Also known as: AI Planning, Automated Planning
Computing sequences of actions to achieve specified goals.
DESCRIPTION
AI planning computes action sequences that transform an initial state into a goal state. Planners use search, heuristics, and domain models (e.g., PDDL) to explore state spaces efficiently. Classical planning assumes deterministic, fully observable environments; extensions handle uncertainty and partial observability. Planning complements learning-based approaches, providing interpretable plans and constraints. In LLM settings, planning structures multi-step tool use to reduce errors. Execution monitoring and replanning address real-world uncertainties.
ALTERNATIVE DEFINITIONS
Wikipedia
Automated planning and scheduling, sometimes denoted as AI planning, is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles.
Anchors planning as an AI branch focused on action sequences.
Planning Wiki
Planning is the computational process of generating a sequence of actions that achieves a goal from an initial state, given a model of the environment.
Highlights model-based generation from initial to goal states.
RELATED TERMS
Search Algorithm Heuristic Goal PDDL STRIPS Policy Markov Decision Process Scheduling Execution Monitoring State Space
COMPETING TERMS
Reactive Control
RELATIONS
- Narrower: Enterprise Resource Planning Scenario Planning
- Referenced by: AgentBench
KNOWLEDGE AREAS
TARGET AUDIENCE
AI Engineer Data Scientist Software Developer
EXTERNAL SOURCES
- Wikipedia - Automated planning and scheduling
- ICAPS - Premier planning community venue
- Planning Wiki - Community knowledge base
- arXiv - Survey on AI planning
TOP QUESTIONS
What is Planning in AI?
Planning computes action sequences from an initial state to a goal. It uses search and heuristics to find feasible, efficient solutions.
Category: Definition
Why is Planning still relevant?
It provides structure, interpretability, and constraint handling for long-horizon tasks. It pairs well with learning and LLM-based reasoning.
Category: Relevancy
What are typical Planning formalisms?
Common ones include STRIPS and PDDL, with extensions for time, resources, and uncertainty.
Category: Concept
How does Planning relate to Search?
Planning frames tasks; search traverses state spaces to find satisfying action sequences. Heuristics guide the search.
Category: Relationship
What is a common Planning mistake?
Poor domain modeling leads to intractable search or brittle plans. Start with minimal viable models and refine iteratively.
Category: Mistakes
How do LLMs use Planning?
LLMs can outline steps, call tools, and revise plans based on feedback, improving reliability on multi-step workflows.
Category: Application
What metrics evaluate Planning?
Plan length, cost, success rate, computation time, and robustness to execution noise are key metrics.
Category: Evaluation
When not to use Planning?
For highly reactive low-latency tasks with simple rules, reactive control may outperform deliberative planning.
Category: Opinion
Where to learn AI Planning?
Explore AIMA chapters, Planning Wiki, and ICAPS tutorials for foundational and advanced topics.
Category: Learning