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Open AccessJournal ArticleDOI

Fast planning through planning graph analysis

Avrim Blum, +1 more
- 01 Feb 1997 - 
- Vol. 90, Iss: 1, pp 281-300
TLDR
Graphplan as mentioned in this paper is a partial-order planner based on constructing and analyzing a compact structure called a planning graph, which can be used to find the shortest possible partial order plan or state that no valid plan exists.
About
This article is published in Artificial Intelligence.The article was published on 1997-02-01 and is currently open access. It has received 1583 citations till now. The article focuses on the topics: Graphplan & Partial-order planning.

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Citations
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Journal ArticleDOI

Planning and Acting in Partially Observable Stochastic Domains

TL;DR: A novel algorithm for solving pomdps off line and how, in some cases, a finite-memory controller can be extracted from the solution to a POMDP is outlined.
Journal ArticleDOI

The FF planning system: fast plan generation through heuristic search

TL;DR: A novel search strategy is introduced that combines hill-climbing with systematic search, and it is shown how other powerful heuristic information can be extracted and used to prune the search space.
Book

Handbook of Constraint Programming

TL;DR: Researchers from other fields should find in this handbook an effective way to learn about constraint programming and to possibly use some of the constraint programming concepts and techniques in their work, thus providing a means for a fruitful cross-fertilization among different research areas.
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Planning as heuristic search

TL;DR: A family of heuristic search planners are studied based on a simple and general heuristic that assumes that action preconditions are independent, which is used in the context of best-first and hill-climbing search algorithms, and tested over a large collection of domains.
Journal ArticleDOI

Logic programs with stable model semantics as a constraint programming paradigm

TL;DR: It is shown that the novel paradigm embeds classical logical satisfiability and standard (finite domain) constraint satisfaction problems but seems to provide a more expressive framework from a knowledge representation point of view.
References
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Book

Introduction to Algorithms

TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Journal ArticleDOI

Strips: A new approach to the application of theorem proving to problem solving

TL;DR: In this paper, the authors describe a problem solver called STRIPS that attempts to find a sequence of operators in a space of world models to transform a given initial world model in which a given goal formula can be proven to be true.
Proceedings Article

Fast planning through planning graph analysis

TL;DR: A new approach to planning in STRIPS-like domains based on constructing and analyzing a compact structure the authors call a Planning Graph is introduced, and a new planner, Graphplan, is described that uses this paradigm.
Proceedings ArticleDOI

A new approach to the maximum flow problem

TL;DR: By incorporating the dynamic tree data structure of Sleator and Tarjan, a version of the algorithm running in O(nm log(n'/m)) time on an n-vertex, m-edge graph is obtained, as fast as any known method for any graph density and faster on graphs of moderate density.
Journal ArticleDOI

Planning for Conjunctive Goals

TL;DR: Theorems that suggest that efficient general purpose planning with more expressive action representations is impossible are presented, and ways to avoid this problem are suggested.