scholarly journals On Guiding Search in HTN Planning with Classical Planning Heuristics

2019 ◽  
Author(s):  
Daniel Höller ◽  
Pascal Bercher ◽  
Gregor Behnke ◽  
Susanne Biundo
Keyword(s):  
Heuristic Search ◽  
State Of The Art ◽  
The State ◽  
Hierarchical Planning ◽  
Htn Planning ◽  
Domain Independent

Planning is the task of finding a sequence of actions that achieves the goal(s) of an agent. It is solved based on a model describing the environment and how to change it. There are several approaches to solve planning tasks, two of the most popular are classical planning and hierarchical planning. Solvers are often based on heuristic search, but especially regarding domain-independent heuristics, techniques in classical planning are more sophisticated. However, due to the different problem classes, it is difficult to use them in hierarchical planning. In this paper we describe how to use arbitrary classical heuristics in hierarchical planning and show that the resulting system outperforms the state of the art in hierarchical planning.

scholarly journals On the Completeness of Pruning Techniques for Planning with Conditional Effects

2013 ◽  
Vol 2013 ◽  
pp. 1-6
Author(s):  
Dunbo Cai ◽  
Sheng Xu ◽  
Tongzhou Zhao ◽  
Yanduo Zhang
Keyword(s):  
Heuristic Search ◽  
State Of The Art ◽  
The State ◽  
Search Procedure ◽  
Conditional Effects ◽  
Relevance Analysis ◽  
Pruning Strategy ◽  
Pruning Techniques

Pruning techniques and heuristics are two keys to the heuristic search-based planning. Thehelpful actionspruning (HAP) strategy andrelaxed-plan-based heuristicsare two representatives among those methods and are still popular in the state-of-the-art planners. Here, we present new analyses on the properties of HAP. Specifically, we show new reasons for which HAP can cause incompleteness of a search procedure. We prove that, in general, HAP is incomplete for planning with conditional effects if factored expansions of actions are used. To preserve completeness, we propose a pruning strategy that is based onrelevance analysisandconfrontation. We will show that bothrelevance analysisandconfrontationare necessary. We call it theconfrontation and goal relevant actionspruning (CGRAP) strategy. However, CGRAP is computationally hard to be exactly computed. Therefore, we suggest practical approximations from the literature.

scholarly journals Semantic Attachments for HTN Planning

2020 ◽  
Vol 34 (06) ◽  
pp. 9933-9940
Author(s):  
Maurício Cecílio Magnaguagno ◽  
Felipe Meneguzzi
Keyword(s):  
Domain Knowledge ◽  
Ad Hoc ◽  
Planning Process ◽  
State Of The Art ◽  
Fixed Number ◽  
The State ◽  
Decomposition Process ◽  
Htn Planning ◽  
Task Networks ◽  
Expensive Process

Hierarchical Task Networks (HTN) planning uses a decomposition process guided by domain knowledge to guide search towards a planning task. While many HTN planners allow calls to external processes (e.g. to a simulator interface) during the decomposition process, this is a computationally expensive process, so planner implementations often use such calls in an ad-hoc way using very specialized domain knowledge to limit the number of calls. Conversely, the classical planners that are capable of using external calls (often called semantic attachments) during planning are limited to generating a fixed number of ground operators at problem grounding time. We formalize Semantic Attachments for HTN planning using semi coroutines, allowing such procedurally defined predicates to link the planning process to custom unifications outside of the planner, such as numerical results from a robotics simulator. The resulting planner then uses such coroutines as part of its backtracking mechanism to search through parallel dimensions of the state-space (e.g. through numeric variables). We show empirically that our planner outperforms the state-of-the-art numeric planners in a number of domains using minimal extra domain knowledge.

scholarly journals Goal Probability Analysis in Probabilistic Planning: Exploring and Enhancing the State of the Art

2016 ◽  
Vol 57 ◽  
pp. 229-271 ◽  
Author(s):  
Marcel Steinmetz ◽  
Jörg Hoffmann ◽  
Olivier Buffet
Keyword(s):  
Heuristic Search ◽  
Resource Constraints ◽  
State Of The Art ◽  
Search Algorithm ◽  
Search Algorithms ◽  
The State ◽  
Probabilistic Planning ◽  
Large Space ◽  
Heuristic Search Algorithms ◽  
Wide Range

Unavoidable dead-ends are common in many probabilistic planning problems, e.g. when actions may fail or when operating under resource constraints. An important objective in such settings is MaxProb, determining the maximal probability with which the goal can be reached, and a policy achieving that probability. Yet algorithms for MaxProb probabilistic planning are severely underexplored, to the extent that there is scant evidence of what the empirical state of the art actually is. We close this gap with a comprehensive empirical analysis. We design and explore a large space of heuristic search algorithms, systematizing known algorithms and contributing several new algorithm variants. We consider MaxProb, as well as weaker objectives that we baptize AtLeastProb (requiring to achieve a given goal probabilty threshold) and ApproxProb (requiring to compute the maximum goal probability up to a given accuracy). We explore both the general case where there may be 0-reward cycles, and the practically relevant special case of acyclic planning, such as planning with a limited action-cost budget. We design suitable termination criteria, search algorithm variants, dead-end pruning methods using classical planning heuristics, and node selection strategies. We design a benchmark suite comprising more than 1000 instances adapted from the IPPC, resource-constrained planning, and simulated penetration testing. Our evaluation clarifies the state of the art, characterizes the behavior of a wide range of heuristic search algorithms, and demonstrates significant benefits of our new algorithm variants.

scholarly journals A Multilingual and Multidomain Study on Dialog Act Recognition Using Character-Level Tokenization

Information ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 94 ◽  
Author(s):  
Eugénio Ribeiro ◽  
Ricardo Ribeiro ◽  
David de Matos
Keyword(s):  
State Of The Art ◽  
Morphological Characteristics ◽  
The State ◽  
Complementary Information ◽  
Dialog Systems ◽  
Word Level ◽  
Morphological Aspects ◽  
Multiple Domains ◽  
Domain Independent ◽  
Multiple Character

Automatic dialog act recognition is an important step for dialog systems since it reveals the intention behind the words uttered by its conversational partners. Although most approaches on the task use word-level tokenization, there is information at the sub-word level that is related to the function of the words and, consequently, their intention. Thus, in this study, we explored the use of character-level tokenization to capture that information. We explored the use of multiple character windows of different sizes to capture morphological aspects, such as affixes and lemmas, as well as inter-word information. Furthermore, we assessed the importance of punctuation and capitalization for the task. To broaden the conclusions of our study, we performed experiments on dialogs in three languages—English, Spanish, and German—which have different morphological characteristics. Furthermore, the dialogs cover multiple domains and are annotated with both domain-dependent and domain-independent dialog act labels. The achieved results not only show that the character-level approach leads to similar or better performance than the state-of-the-art word-level approaches on the task, but also that both approaches are able to capture complementary information. Thus, the best results are achieved by combining tokenization at both levels.

On divergence-based author obfuscation: An attack on the state of the art in statistical authorship verification

2020 ◽  
Vol 62 (2) ◽  
pp. 99-115
Author(s):  
Janek Bevendorff ◽  
Tobias Wenzel ◽  
Martin Potthast ◽  
Matthias Hagen ◽  
Benno Stein
Keyword(s):  
Heuristic Search ◽  
Comprehensive Evaluation ◽  
State Of The Art ◽  
The State ◽  
Writing Style ◽  
Text Quality ◽  
Authorship Verification ◽  
Text Length ◽  
N Gram ◽  
New Algorithms

AbstractAuthorship verification is the task of determining whether two texts were written by the same author based on a writing style analysis. Author obfuscation is the adversarial task of preventing a successful verification by altering a text’s style so that it does not resemble that of its original author anymore. This paper introduces new algorithms for both tasks and reports on a comprehensive evaluation to ascertain the merits of the state of the art in authorship verification to withstand obfuscation.After introducing a new generalization of the well-known unmasking algorithm for short texts, thus completing our collection of state-of-the-art algorithms for verification, we introduce an approach that (1) models writing style difference as the Jensen-Shannon distance between the character n-gram distributions of texts, and (2) manipulates an author’s writing style in a sophisticated manner using heuristic search. For obfuscation, we explore the huge space of textual variants in order to find a paraphrased version of the to-be-obfuscated text that has a sufficiently high Jensen-Shannon distance at minimal costs in terms of text quality loss. We analyze, quantify, and illustrate the rationale of this approach, define paraphrasing operators, derive text length-invariant thresholds for termination, and develop an effective obfuscation framework. Our authorship obfuscation approach defeats the presented state-of-the-art verification approaches, while keeping text changes at a minimum. As a final contribution, we discuss and experimentally evaluate a reverse obfuscation attack against our obfuscation approach as well as possible remedies.

scholarly journals Solving Moving-Blocks Problems

2017 ◽  
Author(s):  
André G. Pereira ◽  
Luciana S. Buriol ◽  
Marcus Ritt
Keyword(s):  
Computational Complexity ◽  
Heuristic Search ◽  
State Of The Art ◽  
The State ◽  
New Methods ◽  
Complexity Results

Moving-blocks problems are extremely hard to solve and a representative abstraction of many applications. Despite their importance, the known computational complexity results are limited to few versions of these problems. In addition, there are no effective methods to optimally solve them. We address both of these issues. This thesis proves the PSPACE-completeness of many versions of moving-blocks problems. Moreover, we propose new methods to optimally solve these problems based on heuristic search with admissible heuristic functions and tie-breaking strategies. Our methods advance the state of the art, create new lines of research and improve the results of applications.

scholarly journals Implicit Abstraction Heuristics

2010 ◽  
Vol 39 ◽  
pp. 51-126 ◽  
Author(s):  
M. Katz ◽  
C. Domshlak
Keyword(s):  
Heuristic Search ◽  
State Of The Art ◽  
Empirical Evaluation ◽  
The State ◽  
Optimal Planning ◽  
Heuristic Function ◽  
Admissible Heuristics ◽  
State Space Search ◽  
Abstract Spaces ◽  
Exponential Size

State-space search with explicit abstraction heuristics is at the state of the art of cost-optimal planning. These heuristics are inherently limited, nonetheless, because the size of the abstract space must be bounded by some, even if a very large, constant. Targeting this shortcoming, we introduce the notion of (additive) implicit abstractions, in which the planning task is abstracted by instances of tractable fragments of optimal planning. We then introduce a concrete setting of this framework, called fork-decomposition, that is based on two novel fragments of tractable cost-optimal planning. The induced admissible heuristics are then studied formally and empirically. This study testifies for the accuracy of the fork decomposition heuristics, yet our empirical evaluation also stresses the tradeoff between their accuracy and the runtime complexity of computing them. Indeed, some of the power of the explicit abstraction heuristics comes from precomputing the heuristic function offline and then determining h(s) for each evaluated state s by a very fast lookup in a ``database.'' By contrast, while fork-decomposition heuristics can be calculated in polynomial time, computing them is far from being fast. To address this problem, we show that the time-per-node complexity bottleneck of the fork-decomposition heuristics can be successfully overcome. We demonstrate that an equivalent of the explicit abstraction notion of a ``database'' exists for the fork-decomposition abstractions as well, despite their exponential-size abstract spaces. We then verify empirically that heuristic search with the ``databased" fork-decomposition heuristics favorably competes with the state of the art of cost-optimal planning.

Practical Picture Processing

1974 ◽  
Vol 32 ◽  
pp. 338-339
Author(s):  
T. A. Welton
Keyword(s):  
Radiation Damage ◽  
Coherence Length ◽  
Spatial Information ◽  
State Of The Art ◽  
Coherent Radiation ◽  
The State ◽  
Energy Spread ◽  
Electron Micrograph ◽  
Picture Processing ◽  
Molecular Skeleton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.

Hypothesis-Evidence Coordination: The State of the Art

2003 ◽  
Vol 48 (6) ◽  
pp. 826-829 ◽  
Author(s):  
Eric Amsel
Keyword(s):  
State Of The Art ◽  
The State

The State of the Art

1968 ◽  
Vol 13 (9) ◽  
pp. 479-480
Author(s):  
LEWIS PETRINOVICH
Keyword(s):  
State Of The Art ◽  
The State
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