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SHOP: Simple Hierarchical Ordered Planner

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TLDR
In the authors' tests, SHOP was several orders of magnitude faster man Blackbox and several times faster than TLpian, even though SHOP is coded in Lisp and the other planners are coded in C.
Abstract
SHOP (Simple Hierarchical Ordered Planner) is a domain-independent HTN planning system with the following characteristics. • SHOP plans for tasks in the same order that they will later be executed. This avoids some goal-interaction issues that arise in other HTN planners, so that the planning algorithm is relatively simple. • Since SHOP knows the complete world-state at each step of the planning process, it can use highly expressive domain representations. For example, it can do planning problems that require complex numeric computations. • In our tests, SHOP was several orders of magnitude faster man Blackbox and several times faster than TLpian, even though SHOP is coded in Lisp and the other planners are coded in C.

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Citations
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HTN Problem Spaces: Structure, Algorithms, Termination.

TL;DR: For HTN planning, this work formally characterize and classify four kinds of problem spaces in which each node represents a planning problem or subproblem.

Planning in Answer Set Programming using Ordered Task Decomposition.

TL;DR: In this paper, a formalism for solving Hierarchical Task Network (HTN) planning using Answer Set Programming (ASP) is introduced, and a translation method from SHOP's representation of the planning problem into logic programs with negation is presented.
Book ChapterDOI

Learning action strategies for planning domains using genetic programming

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Finding Optimal Solutions in HTN Planning - A SAT-based Approach

TL;DR: This work shows how the currently bestperforming approach to HTN planning – the translation into propositional logic – can be utilised to find optimal plans and proposes an optimal SAT-based HTN planner that performs favourably on a benchmark set.
Proceedings Article

Using planning graphs for solving HTN planning problems

TL;DR: This paper presents the GraphHTN algorithm, a hybrid planning algorithm that does Hierarchical.
References
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Book

A Structure for Plans and Behavior

TL;DR: Progress to date in the ability of a computer system to understand and reason about actions is described, and the structure of a plan of actions is as important for problem solving and execution monitoring as the nature of the actions themselves.
Proceedings Article

UCPOP: a sound, complete, partial order planner for ADL

TL;DR: It is proved ucpop is both sound and complete for this representation and a practical implementation that succeeds on all of Pednault's and McDermott's examples, including the infamous "Yale Stacking Problem".
Proceedings Article

Generating project networks

TL;DR: The planner (NONLIN) and the Task Formalism (TF) used to hierarchically specify a domain are described, which can aid in the generation of project networks.
Journal ArticleDOI

Using temporal logics to express search control knowledge for planning

TL;DR: This work shows how domain dependent search control knowledge can be represented in a temporal logic, and then utilized to effectively control a forward-chaining planner.
Proceedings Article

Systematic nonlinear planning

TL;DR: A simple, sound, complete, and systematic algorithm for domain independent STRIPS planning by starting with a ground procedure and then applying a general, and independently verifiable, lifting transformation.
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