computer science

Hierarchical task network

Hierarchical task network is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Hierarchical task network rather than just read about it. In short: In artificial intelligence, hierarchical task network (HTN) planning is an approach to automated planning in which the dependency among actions can be given in the form of hierarchically structured networks. Planning problems are specified in the hierarchical task network approach by providing a set of tasks, which can be: primitive (initial state) tasks, which roughly correspond to the actions of STRIPS; compound t…

Key takeaways

Hierarchical task network belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Hierarchical task network to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Hierarchical task network from memory before moving on to harder problems.

Reference excerpt

In artificial intelligence, hierarchical task network (HTN) planning is an approach to automated planning in which the dependency among actions can be given in the form of hierarchically structured networks. Planning problems are specified in the hierarchical task network approach by providing a set of tasks, which can be:

primitive (initial state) tasks, which roughly correspond to the actions of STRIPS; compound tasks (intermediate state), which can be seen as composed of a set of simpler tasks; goal tasks (goal state), which roughly corresponds to the goals of STRIPS, but are more general. A solution to an HTN problem is then an executable sequence of primitive tasks that can be obtained from the initial task network by decomposing compound tasks into their set of simpler tasks, and by inserting ordering constraints. A primitive task is an action that can be executed directly given the state in which it is executed supports its precondition. A compound task is a complex task composed of a partially ordered set of further tasks, which can either be primitive or abstract. A goal task is a task of satisfying a condition. The difference between primitive and other tasks is that the primitive actions can be directly executed. Compound and goal tasks both require a sequence of primitive actions to be performed; however, goal tasks are specified in terms of conditions that have to be made true, while compound tasks can only be specified in terms of other tasks via the task network outlined below. Constraints among tasks are expressed in the form of networks, called (hierarchical) task networks. A task network is a set of tasks and constraints among them. Such a network can be used as the precondition for another compound or goal task to be feasible. This way, one can express that a given task is feasible only if a set of other actions (those mentioned in the network) are done, and they are done in such a way that the constraints among them (specified by the network) are satisfied. One particular formalism for representing hierarchical task networks that has been fairly widely used is TAEMS. Some of the best-known domain-independent HTN-planning systems are:

NOAH, Nets of Action Hierarchies. Nonlin, one of the first HTN planning systems. SIPE-2 O-Plan, Open Planning Architecture UMCP, the first probably sound and complete HTN planning systems. I-X/I-Plan SHOP2, a HTN-planner developed at University of Maryland, College Park. PANDA, a system designed for hybrid planning, an extension of HTN planning developed at Ulm University, Germany. HTNPlan-P, preference-based HTN planning. HTN planning is strictly more expressive than STRIPS, to the point of being undecidable in the general case. However, many syntactic restrictions of HTN planning are decidable, with known complexities ranging from NP-complete to 2-EXPSPACE-complete, and some HTN problems can be efficiently compiled into PDDL, a STRIPS-like language.

See also STRIPS Hierarchical control system - a feedback control system well suited for HTN planning

References

Worked examples

Example 1 — a first encounter with Hierarchical task network

Start with the simplest possible case. Write down what Hierarchical task network claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Hierarchical task network before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Hierarchical task network ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Hierarchical task network

In research: Hierarchical task network appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Hierarchical task network in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Hierarchical task network is common in secondary-school and first-year university syllabi. It links to neighbouring topics Automated planning and scheduling, so understanding it makes those chapters shorter.
In everyday life: Look for Hierarchical task network outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Hierarchical task network in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Hierarchical task network means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Hierarchical task network out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Hierarchical task network in simple terms?

Why does Hierarchical task network matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Hierarchical task network?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Hierarchical task network.