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Fast Planning Through Planning Graph Analysis
 ARTIFICIAL INTELLIGENCE
, 1995
"... We introduce a new approach to planning in STRIPSlike domains based on constructing and analyzing a compact structure we call a Planning Graph. We describe a new planner, Graphplan, that uses this paradigm. Graphplan always returns a shortest possible partialorder plan, or states that no valid pla ..."
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Cited by 1165 (3 self)
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We introduce a new approach to planning in STRIPSlike domains based on constructing and analyzing a compact structure we call a Planning Graph. We describe a new planner, Graphplan, that uses this paradigm. Graphplan always returns a shortest possible partialorder plan, or states that no valid
PartialOrder Methods for the Verification of Concurrent Systems  An Approach to the StateExplosion Problem
, 1995
"... Statespace exploration techniques are increasingly being used for debugging and proving correct finitestate concurrent reactive systems. The reason for this success is mainly the simplicity of these techniques. Indeed, they are easy to understand, easy to implement and, last but not least, easy to ..."
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Cited by 362 (11 self)
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Statespace exploration techniques are increasingly being used for debugging and proving correct finitestate concurrent reactive systems. The reason for this success is mainly the simplicity of these techniques. Indeed, they are easy to understand, easy to implement and, last but not least, easy to use: they are fully automatic. Moreover, the range of properties that they can verify has been substantially broadened thanks to the development of modelchecking methods for various temporal logics. The main limit of statespace exploration verification techniques is the often excessive size of the state space due, among other causes, to the modeling of concurrency by interleaving. However, exploring all interleavings of concurrent events is not a priori necessary for verification: interleavings corresponding to the same concurrent execution contain related information. One can thus hope to be able to verify properties of a concurrent system without exploring all interleavings of its concu...
PartialOrder Planning: Evaluating Possible Efficiency Gains
 Artificial Intelligence
, 1994
"... Although most people believe that planners that delay stepordering decisions as long as possible are more efficient than those that manipulate totally ordered sequences of actions, this intuition has received little formal justification or empirical validation. In this paper we do both, characteriz ..."
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Cited by 75 (1 self)
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, characterizing the types of domains that offer performance differentiation and the features that distinguish the relative overhead of three planning algorithms. As expected, the partialorder (nonlinear) planner often has an advantage when confronted with problems in which the specific order of the plan steps
Finding the k Shortest Paths
, 1997
"... We give algorithms for finding the k shortest paths (not required to be simple) connecting a pair of vertices in a digraph. Our algorithms output an implicit representation of these paths in a digraph with n vertices and m edges, in time O(m + n log n + k). We can also find the k shortest pat ..."
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Cited by 401 (2 self)
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We give algorithms for finding the k shortest paths (not required to be simple) connecting a pair of vertices in a digraph. Our algorithms output an implicit representation of these paths in a digraph with n vertices and m edges, in time O(m + n log n + k). We can also find the k shortest
Planning Algorithms
, 2004
"... This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning ..."
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Cited by 1108 (51 self)
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This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning
UCPOP: A Sound, Complete, Partial Order Planner for ADL
, 1992
"... We describe the ucpop partial order planning algorithm which handles a subset of Pednault's ADL action representation. In particular, ucpop operates with actions that have conditional effects, universally quantified preconditions and effects, and with universally quantified goals. We prove ucpo ..."
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Cited by 491 (24 self)
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We describe the ucpop partial order planning algorithm which handles a subset of Pednault's ADL action representation. In particular, ucpop operates with actions that have conditional effects, universally quantified preconditions and effects, and with universally quantified goals. We prove
Derivation Replay for PartialOrder Planning
 In Proceedings AAAI94
, 1994
"... Derivation replay was first proposed by Carbonell as a method of transferring guidance from a previous problemsolving episode to a new one. Subsequent implementations have used statespace planning as the underlying methodology. This paper is motivated by the acknowledged superiority of partialord ..."
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Cited by 23 (6 self)
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Derivation replay was first proposed by Carbonell as a method of transferring guidance from a previous problemsolving episode to a new one. Subsequent implementations have used statespace planning as the underlying methodology. This paper is motivated by the acknowledged superiority of partialorder
The FF planning system: Fast plan generation through heuristic search
 Journal of Artificial Intelligence Research
, 2001
"... We describe and evaluate the algorithmic techniques that are used in the FF planning system. Like the HSP system, FF relies on forward state space search, using a heuristic that estimates goal distances by ignoring delete lists. Unlike HSP's heuristic, our method does not assume facts to be ind ..."
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Cited by 822 (53 self)
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We describe and evaluate the algorithmic techniques that are used in the FF planning system. Like the HSP system, FF relies on forward state space search, using a heuristic that estimates goal distances by ignoring delete lists. Unlike HSP's heuristic, our method does not assume facts
Derivation Replay for PartialOrder Planning
"... Derivation replay was first proposed by Carbonell as a method of transferring guidancefrom a previous problemsolving episode to a new one. Subsequent implementations have used statespace planning as the underlying methodology. This paper is motivated by the acknowledged superiority of partial ..."
Abstract
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Derivation replay was first proposed by Carbonell as a method of transferring guidancefrom a previous problemsolving episode to a new one. Subsequent implementations have used statespace planning as the underlying methodology. This paper is motivated by the acknowledged superiority of partialorder
Graphs over Time: Densification Laws, Shrinking Diameters and Possible Explanations
, 2005
"... How do real graphs evolve over time? What are “normal” growth patterns in social, technological, and information networks? Many studies have discovered patterns in static graphs, identifying properties in a single snapshot of a large network, or in a very small number of snapshots; these include hea ..."
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Cited by 534 (48 self)
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How do real graphs evolve over time? What are “normal” growth patterns in social, technological, and information networks? Many studies have discovered patterns in static graphs, identifying properties in a single snapshot of a large network, or in a very small number of snapshots; these include heavy tails for in and outdegree distributions, communities, smallworld phenomena, and others. However, given the lack of information about network evolution over long periods, it has been hard to convert these findings into statements about trends over time. Here we study a wide range of real graphs, and we observe some surprising phenomena. First, most of these graphs densify over time, with the number of edges growing superlinearly in the number of nodes. Second, the average distance between nodes often shrinks over time, in contrast to the conventional wisdom that such distance parameters should increase slowly as a function of the number of nodes (like O(log n) orO(log(log n)). Existing graph generation models do not exhibit these types of behavior, even at a qualitative level. We provide a new graph generator, based on a “forest fire” spreading process, that has a simple, intuitive justification, requires very few parameters (like the “flammability” of nodes), and produces graphs exhibiting the full range of properties observed both in prior work and in the present study.
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