Open AccessProceedings Article
SHOP: Simple Hierarchical Ordered Planner
Dana S. Nau,Yue Cao,Amnon Lotem,Héctor Muñoz-Avila +3 more
- pp 968-975
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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.read more
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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.
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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".
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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
Fahiem Bacchus,Froduald Kabanza +1 more
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.
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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.