scholarly journals Characterizing polynomial Ramsey quantifiers

2019 ◽  
Vol 29 (06) ◽  
pp. 896-908
Author(s):  
Ronald de Haan ◽  
Jakub Szymanik

AbstractRamsey quantifiers are a natural object of study not only for logic and computer science but also for the formal semantics of natural language. Restricting attention to finite models leads to the natural question whether all Ramsey quantifiers are either polynomial-time computable or NP-hard, and whether we can give a natural characterization of the polynomial-time computable quantifiers. In this paper, we first show that there exist intermediate Ramsey quantifiers and then we prove a dichotomy result for a large and natural class of Ramsey quantifiers, based on a reasonable and widely believed complexity assumption. We show that the polynomial-time computable quantifiers in this class are exactly the constant-log-bounded Ramsey quantifiers.

1996 ◽  
Vol 07 (01) ◽  
pp. 23-41
Author(s):  
MARTIN FÜRER ◽  
WEBB MILLER

An alignment of k given sequences is a k-rowed matrix frequently used by molecular biologists to display correspondences between entries from each sequence. Under one approach, an alignment is represented by a matrix of ‘x’ and ’-’ characters, where each x in row r indicates the position of an entry of sequence r. It is sometimes efficient to store only the run-length encoding of each row of this bit-matrix. A natural class of commands for editing one such row into another consists of operations of the form: “Move the d dashes that begin at position i of row r to position j of that row,” for relevant values of r, d, i and j. We show that the problem of determining a shortest sequence of such operations that converts one given alignment to another is NP-hard and give a polynomial-time algorithm that always comes within a factor 5/4 of optimality. An application of these ideas to alignments of long DNA sequences is discussed.


2020 ◽  
Vol 54 (4) ◽  
pp. 1027-1040
Author(s):  
Doost Ali Mojdeh ◽  
Babak Samadi ◽  
Ismael G. Yero

In this paper we define the global defensive k-alliance (number) in a digraph D, and give several bounds on this parameter with characterizations of all digraphs attaining the bounds. In particular, for the case k = −1, we give a lower (an upper) bound on this parameter for directed trees (rooted trees). Moreover, the characterization of all directed trees (rooted trees) for which the equality holds is given. Finally, we show that the problem of finding the global defensive k-alliance number of a digraph is NP-hard for any suitable non-negative value of k, and in contrast with it, we also show that finding a minimum global defensive (−1)-alliance for any rooted tree is polynomial-time solvable.


10.29007/v68w ◽  
2018 ◽  
Author(s):  
Ying Zhu ◽  
Mirek Truszczynski

We study the problem of learning the importance of preferences in preference profiles in two important cases: when individual preferences are aggregated by the ranked Pareto rule, and when they are aggregated by positional scoring rules. For the ranked Pareto rule, we provide a polynomial-time algorithm that finds a ranking of preferences such that the ranked profile correctly decides all the examples, whenever such a ranking exists. We also show that the problem to learn a ranking maximizing the number of correctly decided examples (also under the ranked Pareto rule) is NP-hard. We obtain similar results for the case of weighted profiles when positional scoring rules are used for aggregation.


2021 ◽  
pp. 1-13
Author(s):  
Lamiae Benhayoun ◽  
Daniel Lang

BACKGROUND: The renewed advent of Artificial Intelligence (AI) is inducing profound changes in the classic categories of technology professions and is creating the need for new specific skills. OBJECTIVE: Identify the gaps in terms of skills between academic training on AI in French engineering and Business Schools, and the requirements of the labour market. METHOD: Extraction of AI training contents from the schools’ websites and scraping of a job advertisements’ website. Then, analysis based on a text mining approach with a Python code for Natural Language Processing. RESULTS: Categorization of occupations related to AI. Characterization of three classes of skills for the AI market: Technical, Soft and Interdisciplinary. Skills’ gaps concern some professional certifications and the mastery of specific tools, research abilities, and awareness of ethical and regulatory dimensions of AI. CONCLUSIONS: A deep analysis using algorithms for Natural Language Processing. Results that provide a better understanding of the AI capability components at the individual and the organizational levels. A study that can help shape educational programs to respond to the AI market requirements.


1986 ◽  
Vol 9 (3) ◽  
pp. 323-342
Author(s):  
Joseph Y.-T. Leung ◽  
Burkhard Monien

We consider the computational complexity of finding an optimal deadlock recovery. It is known that for an arbitrary number of resource types the problem is NP-hard even when the total cost of deadlocked jobs and the total number of resource units are “small” relative to the number of deadlocked jobs. It is also known that for one resource type the problem is NP-hard when the total cost of deadlocked jobs and the total number of resource units are “large” relative to the number of deadlocked jobs. In this paper we show that for one resource type the problem is solvable in polynomial time when the total cost of deadlocked jobs or the total number of resource units is “small” relative to the number of deadlocked jobs. For fixed m ⩾ 2 resource types, we show that the problem is solvable in polynomial time when the total number of resource units is “small” relative to the number of deadlocked jobs. On the other hand, when the total number of resource units is “large”, the problem becomes NP-hard even when the total cost of deadlocked jobs is “small” relative to the number of deadlocked jobs. The results in the paper, together with previous known ones, give a complete delineation of the complexity of this problem under various assumptions of the input parameters.


2021 ◽  
pp. 1-37
Author(s):  
Phan Minh Thang ◽  
Phan Minh Dung ◽  
Jiraporn Pooksook
Keyword(s):  

We study the semantics of dialectical proof procedures. As dialectical proof procedures are in general sound but not complete wrt admissibility semantics, a natural question here is whether we could give a more precise semantical characterization of what they compute. Based on a new notion of infinite arguments representing (possibly infinite) loops, we introduce a stricter notion of admissibility, referred to as strict admissibility, and show that dialectical proof procedures are in general sound and complete wrt strict admissibility.


Designs ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 42
Author(s):  
Eric Lazarski ◽  
Mahmood Al-Khassaweneh ◽  
Cynthia Howard

In recent years, disinformation and “fake news” have been spreading throughout the internet at rates never seen before. This has created the need for fact-checking organizations, groups that seek out claims and comment on their veracity, to spawn worldwide to stem the tide of misinformation. However, even with the many human-powered fact-checking organizations that are currently in operation, disinformation continues to run rampant throughout the Web, and the existing organizations are unable to keep up. This paper discusses in detail recent advances in computer science to use natural language processing to automate fact checking. It follows the entire process of automated fact checking using natural language processing, from detecting claims to fact checking to outputting results. In summary, automated fact checking works well in some cases, though generalized fact checking still needs improvement prior to widespread use.


Author(s):  
Ranya Ahmed Rashid Shaheen, Abdelrahman Mudawi Abdelrahim Al Ranya Ahmed Rashid Shaheen, Abdelrahman Mudawi Abdelrahim Al

The object of inquiry in Linguistics is the human ability to acquire and use a natural language, and the goal of linguistic theory is an explicit characterization of that ability. Looking at the communicative abilities of other species, it becomes clear that our linguistic ability is specific to our species, undoubtedly a product of our biology. But how do we go about determining the specifics of this Language faculty? _here are two primary ways in which we infer the nature of Language from the properties of individual languages: arguments from the Poverty of the Stimulus, and the search for universals that characterize every natural language. Arguments of the first sort are not easy to construct (though not as difficult as sometimes suggested), and apply only to a tiny part of Language as a whole. Arguments from universals or typological generalizations are also quite problematic. In phonology, morphology, and syntax, factors of historical development, functional underpinnings, limitations of the learning situation, among others conspire to compromise the explanatory value of arguments from observed cross-linguistic regularities. Confounding the situation is the likelihood that properties found across languages as a consequence of such external forces have been incorporated into the Language faculty evolutionarily through the ‘Baldwin Effect.’ _e conflict between the biologically based specificity of the human Language faculty and the difficulty of establishing most of its properties in a secure way cannot, however, be avoided by ignoring or denying the reality of either of its poles.


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