Relevant bibliographies by topics / Approximate logics

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Approximate logics'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Approximate logics"

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Biacino, Loredana, and Giangiacomo Gerla. "Logics with approximate premises." International Journal of Intelligent Systems 13, no. 1 (January 1998): 1–10. http://dx.doi.org/10.1002/(sici)1098-111x(199801)13:1<1::aid-int1>3.0.co;2-u.

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Dunin-Kęplicz, Barbara, Anh Nguyen, and Andrzej Szałas. "A layered rule-based architecture for approximate knowledge fusion?" Computer Science and Information Systems 7, no. 3 (2010): 617–42. http://dx.doi.org/10.2298/csis100209015d.

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In this paper we present a framework for fusing approximate knowledge obtained from various distributed, heterogenous knowledge sources. This issue is substantial in modeling multi-agent systems, where a group of loosely coupled heterogeneous agents cooperate in achieving a common goal. In paper [5] we have focused on defining general mechanism for knowledge fusion. Next, the techniques ensuring tractability of fusing knowledge expressed as a Horn subset of propositional dynamic logic were developed in [13,16]. Propositional logics may seem too weak to be useful in real-world applications. On the other hand, propositional languages may be viewed as sublanguages of first-order logics which serve as a natural tool to define concepts in the spirit of description logics [2]. These notions may be further used to define various ontologies, like e.g. those applicable in the Semantic Web. Taking this step, we propose a framework, in which our Horn subset of dynamic logic is combined with deductive database technology. This synthesis is formally implemented in the framework of HSPDL architecture. The resulting knowledge fusion rules are naturally applicable to real-world data.
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Esteva, Francesc, Lluís Godo, Ricardo O. Rodríguez, and Thomas Vetterlein. "Logics for approximate and strong entailments." Fuzzy Sets and Systems 197 (June 2012): 59–70. http://dx.doi.org/10.1016/j.fss.2011.09.005.

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Lemström, Kjell, and Lauri Hella. "Approximate pattern matching and transitive closure logics." Theoretical Computer Science 299, no. 1-3 (April 2003): 387–412. http://dx.doi.org/10.1016/s0304-3975(02)00484-x.

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Liau, Churn-Jung. "Possibilistic Residuated Implication Logics with Applications." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 06, no. 04 (August 1998): 365–85. http://dx.doi.org/10.1142/s0218488598000306.

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In this paper, we will develop a class of logics for reasoning about qualitative and quantitative uncertainty. The semantics of the logics is uniformly based on possibility theory. Each logic in the class is parameterized by a t-norm operation on [0,1], and we express the degree of implication between the possibilities of two formulas explicitly by using residuated implication with respect to the t-norm. The logics are then shown to be applicable to possibilistic reasoning, approximate reasoning, and nonmonotonic reasoning.
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Vetterlein, Thomas, Francesc Esteva, and Lluís Godo. "Logics for Approximate Entailment in ordered universes of discourse." International Journal of Approximate Reasoning 71 (April 2016): 50–63. http://dx.doi.org/10.1016/j.ijar.2016.02.001.

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Jiang, Yuncheng, Ju Wang, Suqin Tang, and Bao Xiao. "Reasoning with rough description logics: An approximate concepts approach." Information Sciences 179, no. 5 (February 2009): 600–612. http://dx.doi.org/10.1016/j.ins.2008.10.021.

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Krynicki, Michał. "A Note on Rough Concepts Logic." Fundamenta Informaticae 13, no. 2 (April 1, 1990): 227–35. http://dx.doi.org/10.3233/fi-1990-13206.

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In papers [4,5] Pawlak introduced the notion of a rough set and approximation space. In [6] Pawlak formulated some concept of rough logic. The notion of the approximate truth was considered by many philosophers and logicians and in the last time by computer scientists. This was motivated by some research in artificial intelligence as for example expert systems, approximate reasoning methods and information system with imprecise information. The concept of rough logic introduced in [6] based on the notion of approximate truth determined by rough sets. Following these ideas Rasiowa and Skowron in [7] proposed the apropriate first order logic for concepts of rough definability. We denote this logic by LR. In [9] Szczerba proposed some logic with additional quantifier as rough concepts logic. We denote this logic by L(QR). The aim of this paper is a comparizing of these two logics with respect to their expressive power and giving some propositions of some modificated versions of rough concepts logics. We use more or less standard notation. By [a]R we denote the equivalence class of the element a with respect to the equivalence relation R. We write L ⩽ L ′ if expressive power of the logic L is weaker then t.he expressive power of the logic L ′ (i.e. each class of models definable by a sentence from L is also definable by a sentence from L ′ ). If L ⩽ L ′ and L ′ ⩽ L then we say that L and L ′ are equivalent and denote this by L ≡ L ′ . If L ⩽ L ′ but L ≢ L ′ then we write L < L ′ .
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Whalen, Thomas, and Brian Schott. "Alternative logics for approximate reasoning in expert systems: a comparative study." International Journal of Man-Machine Studies 22, no. 3 (March 1985): 327–46. http://dx.doi.org/10.1016/s0020-7373(85)80007-9.

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Feng, Zhi-Qiang, and Cun-Gen Liu. "On vague logics and approximate reasoning based on vague linear transformation." International Journal of Systems Science 43, no. 9 (September 2012): 1591–602. http://dx.doi.org/10.1080/00207721.2010.549579.

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Dissertations / Theses on the topic "Approximate logics"

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Rajaratnam, David Computer Science &amp Engineering Faculty of Engineering UNSW. "Logical approximation and compilation for resource-bounded reasoning." Publisher:University of New South Wales. Computer Science & Engineering, 2008. http://handle.unsw.edu.au/1959.4/41296.

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Providing a logical characterisation of rational agent reasoning has been a long standing challenge in artificial intelligence (AI) research. It is a challenge that is not only of interest for the construction of AI agents, but is of equal importance in the modelling of agent behaviour. The goal of this thesis is to contribute to the formalisation of agent reasoning by showing that the computational limitations of agents is a vital component of modelling rational behaviour. To achieve this aim, both motivational and formal aspects of resource-bounded agents are examined. It is a central argument of this thesis that accounting for computational limitations is critical to the success of agent reasoning, yet has received only limited attention from the broader research community. Consequently, an important contribution of this thesis is in its advancing of motivational arguments in support of the need to account for computational limitations in agent reasoning research. As a natural progression from the motivational arguments, the majority of this thesis is devoted to an examination of propositional approximate logics. These logics represent a step towards the development of resource-bounded agents, but are also applicable to other areas of automated reasoning. This thesis makes a number of contributions in mapping the space of approximate logics. In particular, it draws a connection between approximate logics and knowledge compilation, by developing an approximate knowledge compilation method based on Cadoli and Schaerf??s S-3 family of approximate logics. This method allows for the incremental compilation of a knowledge base, thus reducing the need for a costly recompilation process. Furthermore, each approximate compilation has well-defined logical properties due to its correspondence to a particular S-3 logic. Important contributions are also made in the examination of approximate logics for clausal reasoning. Clausal reasoning is of particular interest due to the efficiency of modern clausal satisfiability solvers and the related research into problem hardness. In particular, Finger's Logics of Limited Bivalence are shown to be applicable to clausal reasoning. This is subsequently shown to logically characterise the behaviour of the well-known DPLL algorithm for determining boolean satisfiability, when subjected to restricted branching.
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Fernández, Gil Oliver. "Adding Threshold Concepts to the Description Logic EL." Doctoral thesis, Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-204523.

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We introduce a family of logics extending the lightweight Description Logic EL, that allows us to define concepts in an approximate way. The main idea is to use a graded membership function m, which for each individual and concept yields a number in the interval [0,1] expressing the degree to which the individual belongs to the concept. Threshold concepts C~t for ~ in {<,<=,>,>=} then collect all the individuals that belong to C with degree ~t. We further study this framework in two particular directions. First, we define a specific graded membership function deg and investigate the complexity of reasoning in the resulting Description Logic tEL(deg) w.r.t. both the empty terminology and acyclic TBoxes. Second, we show how to turn concept similarity measures into membership degree functions. It turns out that under certain conditions such functions are well-defined, and therefore induce a wide range of threshold logics. Last, we present preliminary results on the computational complexity landscape of reasoning in such a big family of threshold logics.
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Carbin, Michael (Michael James). "Logical reasoning for approximate and unreliable computation." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/99813.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 343-350).
Improving program performance and resilience are long-standing goals. Traditional approaches include a variety of transformation, compilation, and runtime techniques that share the common property that the resulting program has the same semantics as the original program. However, researchers have recently proposed a variety of new techniques that set aside this traditional restriction and instead exploit opportunities to change the semantics of programs to improve performance and resilience. Techniques include skipping portions of a program's computation, selecting different implementations of program's subcomputations, executing programs on unreliable hardware, and synthesizing values to enable programs to skip or execute through otherwise fatal errors. A major barrier to the acceptance these techniques in both the broader research community and in industrial practice is the challenge that the resulting programs may exhibit behaviors that differ from that of the original program, potentially jeopardizing the program's resilience, safety, and accuracy. This thesis presents the first general programming systems for precisely verifying and reasoning about the programs that result from these techniques. This thesis presents a programming language and program logic for verifying worst-case properties of a transformed program. Specifically the framework, enables verifying that a transformed program satisfies important assertions about its safety (e.g., that it does not access invalid memory) and accuracy (e.g., that it returns a result within a bounded distance of that of the original program). This thesis also presents a programming language and automated analysis for verifying a program's quantitative reliability - the probability the transformed program returns the same result as the original program - when executed on unreliable hardware. The results of this thesis, which include programming languages, program logics, program analysis, and applications thereof, present the first steps toward reaping the benefits of changing the semantics of programs in a beneficial yet principled way.
by Michael James Carbin.
Ph. D.
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Weydert, Emil. "How to approximate the naive comprehension scheme inside of classical logic." Bonn : [s.n.], 1989. http://catalog.hathitrust.org/api/volumes/oclc/19990751.html.

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Taleb-Bendiab, Azzelarabe. "Logic programming for conceptual engineering design : selection process by approximate matching." Thesis, University of Liverpool, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.316548.

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Perundurai, Rajasekaran Siddharthan. "Nonparametric Inverse Reinforcement Learning and Approximate Optimal Control with Temporal Logic Tasks." Digital WPI, 2017. https://digitalcommons.wpi.edu/etd-theses/1205.

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"This thesis focuses on two key problems in reinforcement learning: How to design reward functions to obtain intended behaviors in autonomous systems using the learning-based control? Given complex mission specification, how to shape the reward function to achieve fast convergence and reduce sample complexity while learning the optimal policy? To answer these questions, the first part of this thesis investigates inverse reinforcement learning (IRL) method with a purpose of learning a reward function from expert demonstrations. However, existing algorithms often assume that the expert demonstrations are generated by the same reward function. Such an assumption may be invalid as one may need to aggregate data from multiple experts to obtain a sufficient set of demonstrations. In the first and the major part of the thesis, we develop a novel method, called Non-parametric Behavior Clustering IRL. This algorithm allows one to simultaneously cluster behaviors while learning their reward functions from demonstrations that are generated from more than one expert/behavior. Our approach is built upon the expectation-maximization formulation and non-parametric clustering in the IRL setting. We apply the algorithm to learn, from driving demonstrations, multiple driver behaviors (e.g., aggressive vs. evasive driving behaviors). In the second task, we study whether reinforcement learning can be used to generate complex behaviors specified in formal logic — Linear Temporal Logic (LTL). Such LTL tasks may specify temporally extended goals, safety, surveillance, and reactive behaviors in a dynamic environment. We introduce reward shaping under LTL constraints to improve the rate of convergence in learning the optimal and probably correct policies. Our approach exploits the relation between reward shaping and actor-critic methods for speeding up the convergence and, as a consequence, reducing training samples. We integrate compositional reasoning in formal methods with actor-critic reinforcement learning algorithms to initialize a heuristic value function for reward shaping. This initialization can direct the agent towards efficient planning subject to more complex behavior specifications in LTL. The investigation takes the initial step to integrate machine learning with formal methods and contributes to building highly autonomous and self-adaptive robots under complex missions."
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Martins, Mayler Gama Alvarenga. "Applications of functional composition for CMOS and emerging technologies." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2015. http://hdl.handle.net/10183/164452.

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Os avanços da indústria de semicondutores nas últimas décadas foram baseados fortemente na contínua redução de tamanho dos dispositivos CMOS fabricados. Os usos de dispositivos CMOS dependem profundamente da lógica de portas E/OU/INV. À medida que os dispositivos CMOS estão atingindo oslimites fisicos, pesquisadores aumento esforço para prolongar a vida útil da tecnologia CMOS. Também é necessário investigar dispositivos alternativos, que em muitos casos implicam no uso de operações lógicas básicas diferentes. Como as ferramentas comerciais de síntese não são capazes de manipular eficientemente estas tecnologias Esta tese de doutorado foca em produzir algoritmos eficientes para projeto de circuitos tanto em CMOS quanto em novas tecnologias, integrando estes algorithmos em fluxos de projeto. Para esta tarefa, aplicamos a técnica da composição functional, para sintetizar eficiente tanto em CMOS quanto em tecnologias emergentes. A composição funcional é uma abordagem de síntese de baixo para cima, provendo flexibilidade para implementar algoritmos com resultados ótimos ou sub-ótimos para diferentes tecnologias. A fim de investigar como a composição funcional se compara às abordagens de síntese estado-da-arte, propomos aplicar esse paradigma de síntese em seis cenários diferentes. Dois deles se concentram em circuitos baseados em CMOS e outros quatro em circuitos baseados em tecnologias emergentes. Em relação a circuitos baseados em CMOS, investigamos a composição funcional para fatoração de funções multi-saídas, aplicadas em um fluxo de resíntese. Também manipulamos funções aproximadas, a fim de sintetizar módulos de redundância tripla aproximada. No que diz respeito as tecnologias emergentes, exploramos a composição funcional através de diodos spintrônicos e outras abordagens promissoras com base em diferentes implementações de lógica: a lógica de limiar, lógica majoritária e lógica de implicação. Resultados apresentam uma melhoria considerável em relação aos métodos estadoda- arte tanto para aplicações CMOS quanto aplicações de tecnologias emergentes, demonstrando a capacidade de lidar com diferentes tecnologias e mostrando a possibilidade de melhorar tecnologias ainda não exploradas.
The advances in semiconductor industry over the last decades have been strongly based on continuous scaling down of dimensions in manufactured CMOS devices. The use of CMOS devices profoundly relies on AND/OR/Inverter logic. As the CMOS scaling is reaching its physical limits, researchers increase the effort to prolong the CMOS life. Also, it is necessary to investigate alternative devices, which in many cases implies the use of different basic logic operations. As the commercial synthesis tools are not able to handle these technologies efficiently, there is an opportunity to research alternative logic implementations better suited for these new devices. This thesis focuses on presenting efficient algorithms to design circuits in both CMOS and new technologies while integrating these algorithms into regular design flows. For this task, we apply the functional composition technique, to efficiently synthesize both CMOS and emerging technologies. The functional composition is a bottom-up synthesis approach, providing flexibility to implement algorithms with optimal or suboptimal results for different technologies. To investigate how the functional composition compares to the state-of-the-art synthesis methods, we propose to apply this synthesis paradigm into six different scenarios. Two of them focus on CMOS-based circuits, and other four are based on emerging technologies. Regarding CMOSbased circuits, we investigate functional composition to investigate multi-output factorization in a circuit resynthesis flow. Also, we manipulate approximate functions to synthesize approximate triple modular redundancy (ATMR) modules. Concerning emerging technologies, we explore functional composition over spin-diode circuits and other promising approaches based on different logic implementations: threshold logic, majority logic, and implication logic. Results present a considerable improvement over the state-of-the-art methods for both CMOS and emerging technologies applications, demonstrating the ability to handle different technologies and showing the possibility to improve technologies not explored yet.
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Chaoued, Nouha. "Représentation et traitement des connaissances en logique multivalente : cas d'une répartition non uniforme des degrés de vérité." Thesis, Montpellier, 2017. http://www.theses.fr/2017MONTS048/document.

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Dans la plupart des activités quotidiennes, l’Homme a tendance à utiliser des connaissances imparfaites. L’imperfection se rapporte à trois volets : l’imprécision, l’incertitude et l’incomplétude. Nous thèse concerne les connaissances imprécises. En particulier, nous nous intéressons au traitement qualitatif de l’information imprécise dans les systèmes à base de connaissances. Diverses approches ont été proposées pour traiter les connaissances imprécises, en particulier, la logique floue et la logique multivalente. Les théories des ensembles flous et des multi-ensembles sont un moyen très approprié pour la représentation et la modélisation de l’imprécision.Notre travail s’inscrit dans le contexte de la logique multivalente. Celle-ci permet de représenter symboliquement des connaissances imprécises en utilisant des expressions adverbiales ordonnées du langage naturel. L’utilisation de ces degrés symboliques est plus compréhensible par les experts. Ce type de représentation de données est indépendant du type de leurs domaines de discours. Ainsi, la manipulation des connaissances abstraites ou faisant référence à des échelles numériques se fait de la même manière.Dans la littérature, le traitement de l’information imprécise repose sur une hypothèse implicite de la répartition uniforme des degrés de vérité sur une échelle de 0 à 1. Néanmoins, dans certains cas, un sous-domaine de cette échelle peut être plus informatif et peut inclure plus de termes. Dans ce cas, l’information est définie par des termes déséquilibrés, c’est-à-dire qui ne sont pas uniformément répartis et/ou symétriques par rapport à un terme milieu. Par exemple, pour l’évaluation des apprenants, il est possible de considérer un seul terme négatif F correspondant à l’échec. Quant à la réussite, elle est décrite par plusieurs valeurs de mention, i.e. D, C, B et A. Ainsi, si le terme D est le seuil de la réussite, il est considéré comme le terme milieu avec un seul terme à sa gauche et trois à sa droite. Il s’agit alors d’un ensemble non uniforme.Dans ce travail, nous nous concentrons sur l'extension de la logique multivalente au cas des ensembles non uniformes. En s'appuyant sur notre étude de l'art, nous proposons de nouvelles approches pour représenter et traiter ces ensembles de termes. Tout d'abord, nous introduisons des algorithmes qui permettent de représenter des termes non uniformes à l'aide de termes uniformes et inversement. Ensuite, nous décrivons une méthode pour utiliser des modificateurs linguistiques initialement définis pour les termes uniformes avec des ensembles de termes non uniformes. Par la suite, nous présentons une approche de raisonnement basée sur le modèle du Modus Ponens Généralisé à l'aide des Modificateurs Symboliques Généralisés. Les modèles proposés sont mis en œuvre dans un nouveau système de décision fondé sur des règles pour la reconnaissance de l'odeur de camphre. Nous développons également un outil pour le diagnostic de l'autisme infantile. Les degrés de sévérité de l'atteinte par ce trouble autistique sont représentés par l'échelle d'évaluation de l'autisme infantile (CARS). Il s'agit d'une échelle non uniforme
In most daily activities, humans use imprecise information derived from appreciation instead of exact measurements to make decisions. Various approaches were proposed to deal with imperfect knowledge, in particular, fuzzy logic and multi-valued logic. In this work, we treat the particular case of imprecise knowledge.Taking into account imprecise knowledge by computer systems is based on their representation by means of linguistic variables. Their values form a set of words expressing the different nuances of the treated information. For example, to judge the beauty of the Mona Lisa or the smell of a flower, it is not possible to give an exact value but an appreciation is given by a term like "beautiful" or "floral".In the literature, dealing with imprecise information relies on an implicit assumption: the distribution of terms is uniform on a scale ranging from 0 to 1. Nevertheless, in some cases, a sub-domain of this scale may be more informative and may include more terms. In this case, knowledge are represented by means of an unbalanced terms set, that is, not uniformly nor symmetrically distributed.We have noticed, in the literature, that in the context of fuzzy logic many researchers have dealt with these term sets. However, it is not the case for multi-valued logic. Thereby, in our work, we aim to establish a methodology to represent and manage this kind of data in the context of multi-valued logic. Two aspects are treated. The first one concerns the representation of terms within an unbalanced multi-set. The second deals with the treatment of such kind of imprecise knowledge, i.e. with symbolic modifiers and in reasoning process.In this work, we focus on unbalanced sets in the context of multi-valued logic. Basing on our study of art, we propose new approaches to represent and treat such term sets. First of all, we introduce algorithms that allow representing unbalanced terms within uniform ones and the inverse way. Then, we describe a method to use linguistic modifiers within unbalanced multi-sets. Afterward, we present a reasoning approach based on the Generalized Modus Ponens model using Generalized Symbolic Modifiers. The proposed models are implemented in a novel rule-based decision system for the camphor odor recognition within unbalanced multi-set. We also develop a tool for child autism diagnosis by means of unbalanced severity degrees of the Childhood Autism Rating Scale (CARS)
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Huster, Todd. "OWL query answering using machine learning." Wright State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=wright1446117806.

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Dena, Ornelas Oscar S. "Fast approximate migration of ground penetrating radar using Kalman estimators and determination of the lithospheric structure of Lake Baikal, Russia." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2008. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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Books on the topic "Approximate logics"

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Elkan, Charles. Incremental, approximate planning: Preliminary report. Toronto: Computer Science Dept., University of Toronto, 1989.

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Gerla, Giangiacomo. Fuzzy Logic: Mathematical Tools for Approximate Reasoning. Dordrecht: Springer Netherlands, 2001.

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Fuzzy logic: Mathematical tools for approximate reasoning. Dordrecht: Kluwer Academic Publishers, 2001.

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Fuzziness and approximate reasoning: Epistemics on uncertainty, expectation and risk in rational behavior. Berlin: Springer, 2009.

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Relander, Sami. Towards approximate reasoning on new software product company success potential estimation: A design science based fuzzy logic expert system. [Helsinki]: Helsinki School of Economics, 2008.

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Jonathan, Barnes. Logic and the imperial Stoa. New York: Brill, 1997.

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Categories and logic in Duns Scotus: An interpretation of Aristotle's Categories in the late thirteenth century. Leiden: Brill, 2002.

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Borzyh, Stanislav. Theory of the possible. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1074108.

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In this book, we are talking about a single principle that permeates every organized entity, regardless of what sphere it belongs to. Everywhere and always, and in accordance with the current circumstances, the process of formation, support and regulation of any complex complexes and ensembles is guided and controlled by the concept of the realizable, which postulates that only what is stable and stable will be realized, and everything else will be discarded as untenable and unbalanced. These patterns and patterns can be traced resolutely at all levels of existence. And the universe, and life, and consciousness, and mind, and culture are arranged and assembled according to these schemes, because it is difficult, if possible, for them to be any other. This paper provides an overview of this type of layout in these areas, as well as the theory of the achievable and accessible itself. Using examples and theoretical considerations, it is shown that the configuration of all reliable and long-lasting structures is approximately the same or very similar, because it obeys a single end-to-end logic of the formation of any similar substances, whatever they touch and wherever they are found. In addition, it is demonstrated that if something in this spirit is objectified in practice, then its nature and properties must be fundamentally the same as what we observe around or extremely close to it. Finally, the view is argued and developed, according to which everything consists of matter, is constituted by it, is reduced only to it, including any non-physical phenomena. It is concluded that all the wealth of the world is subject to the same laws of its construction, and all this construction observes the universal rules of the functioning of complex things, no matter what they are aimed at. For all those interested in philosophy.
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Gerla, G. Fuzzy Logic: Mathematical Tools for Approximate Reasoning. Springer, 2013.

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Gerla, G. Fuzzy Logic: Mathematical Tools for Approximate Reasoning (Trends in Logic). Springer, 2001.

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Book chapters on the topic "Approximate logics"

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Yadav, Nitin, and Sebastian Sardina. "Qualitative Approximate Behavior Composition." In Logics in Artificial Intelligence, 450–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33353-8_35.

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Hájek, Petr. "On logics of approximate reasoning." In Knowledge Representation and Reasoning Under Uncertainty, 17–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-58095-6_2.

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Hájek, P. "On Logics of Approximate Reasoning II." In Proceedings of the ISSEK94 Workshop on Mathematical and Statistical Methods in Artificial Intelligence, 147–55. Vienna: Springer Vienna, 1995. http://dx.doi.org/10.1007/978-3-7091-2690-5_10.

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Godo, Lluís. "Similarity-Based Logics for Approximate Entailments." In Quantitative Logic and Soft Computing 2016, 5–6. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46206-6_2.

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Finger, Marcelo, and Renata Wassermann. "Logics for Approximate Reasoning: Approximating Classical Logic “From Above”." In Advances in Artificial Intelligence, 21–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36127-8_3.

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Baader, Franz, Pavlos Marantidis, and Alexander Okhotin. "Approximate Unification in the Description Logic $$\mathcal {FL}_0$$." In Logics in Artificial Intelligence, 49–63. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48758-8_4.

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Mandal, Sudin, Namrata Bhattacharyya, and Swapan Raha. "Approximate Reasoning Under Type-2 Fuzzy Logics." In Springer Proceedings in Mathematics & Statistics, 87–97. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2301-6_7.

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Darwiche, Adnan. "Relax, Compensate and Then Recover: A Theory of Anytime, Approximate Inference." In Logics in Artificial Intelligence, 7–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15675-5_2.

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Hashemi, Soheil, Hokchhay Tann, and Sherief Reda. "Approximate Logic Synthesis Using Boolean Matrix Factorization." In Approximate Circuits, 141–54. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99322-5_7.

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Gerla, Giangiacomo. "Approximate Reasoning." In Fuzzy Logic, 69–87. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9660-2_4.

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Conference papers on the topic "Approximate logics"

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Liu, Gai, and Zhiru Zhang. "Statistically certified approximate logic synthesis." In 2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD). IEEE, 2017. http://dx.doi.org/10.1109/iccad.2017.8203798.

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Bernasconi, Anna, Valentina Ciriani, and Tiziano Villa. "Approximate Logic Synthesis by Symmetrization." In 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2019. http://dx.doi.org/10.23919/date.2019.8715286.

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Meng, Chang, Weikang Qian, and Alan Mishchenko. "ALSRAC: Approximate Logic Synthesis by Resubstitution with Approximate Care Set." In 2020 57th ACM/IEEE Design Automation Conference (DAC). IEEE, 2020. http://dx.doi.org/10.1109/dac18072.2020.9218627.

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van Bremen, Timothy, and Ondrej Kuzelka. "Approximate Weighted First-Order Model Counting: Exploiting Fast Approximate Model Counters and Symmetry." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/587.

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Abstract:
We study the symmetric weighted first-order model counting task and present ApproxWFOMC, a novel anytime method for efficiently bounding the weighted first-order model count of a sentence given an unweighted first-order model counting oracle. The algorithm has applications to inference in a variety of first-order probabilistic representations, such as Markov logic networks and probabilistic logic programs. Crucially for many applications, no assumptions are made on the form of the input sentence. Instead, the algorithm makes use of the symmetry inherent in the problem by imposing cardinality constraints on the number of possible true groundings of a sentence's literals. Realising the first-order model counting oracle in practice using the approximate hashing-based model counter ApproxMC3, we show how our algorithm is competitive with existing approximate and exact techniques for inference in first-order probabilistic models. We additionally provide PAC guarantees on the accuracy of the bounds generated.
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Henzinger, Thomas A., and N. Ege Sarac. "Quantitative and Approximate Monitoring." In 2021 36th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS). IEEE, 2021. http://dx.doi.org/10.1109/lics52264.2021.9470547.

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Yang, Yu-Shen, Subarna Sinha, Andreas Veneris, and Robert K. Brayton. "Automating Logic Rectification by Approximate SPFDs." In 2007 Asia and South Pacific Design Automation Conference. IEEE, 2007. http://dx.doi.org/10.1109/aspdac.2007.358019.

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Yang, Y. S., S. Sinha, A. Veneris, R. K. Brayton, and D. Smith. "Sequential logic rectifications with approximate SPFDs." In 2009 Design, Automation & Test in Europe Conference & Exhibition (DATE'09). IEEE, 2009. http://dx.doi.org/10.1109/date.2009.5090936.

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yin, Hao-kai, and Yin-shui Xia. "Approximate logic optimization for ISFPRM function." In 2018 14th IEEE International Conference on Solid-State and Integrated Circuit Technology (ICSICT). IEEE, 2018. http://dx.doi.org/10.1109/icsict.2018.8564851.

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Taylor, Julia M., and Lawrence J. Mazlack. "Description Logic-Based Approximate Joke Comparison." In 2006 Annual Meeting of the North American Fuzzy Information Processing Society. IEEE, 2006. http://dx.doi.org/10.1109/nafips.2006.365428.

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Yao, Yue, Shuyang Huang, Chen Wang, Yi Wu, and Weikang Qian. "Approximate Disjoint Bi-Decomposition and Its Application to Approximate Logic Synthesis." In 2017 IEEE 35th International Conference on Computer Design (ICCD). IEEE, 2017. http://dx.doi.org/10.1109/iccd.2017.90.

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Reports on the topic "Approximate logics"

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Schwartz, Daniel. Approximate reasoning, logics for self-reference, and the use of nonclassical logics in systems modeling. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.591.

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