Academic literature on the topic 'Quantitative and logical reasoning'
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Journal articles on the topic "Quantitative and logical reasoning"
Warsitasari, Wahyu Dwi, and Imam Rofiki. "UTILIZING GEOGEBRA FOR SOLVING ECONOMIC MATHEMATICS PROBLEMS: PROMOTING LOGICAL REASONING IN PROBLEM-BASED LEARNING." AKSIOMA: Jurnal Program Studi Pendidikan Matematika 12, no. 3 (September 30, 2023): 3445. http://dx.doi.org/10.24127/ajpm.v12i3.7300.
Full textRahmawati, Rahmawati, Edy Kurniawan, and A. Muafiah Nur. "Identifikasi Kemampuan Berpikir Logis Mahasiswa Calon Guru Fisika Menggunakan Instrument TOLT." Jurnal Pendidikan Fisika dan Teknologi 7, no. 1 (June 20, 2021): 27. http://dx.doi.org/10.29303/jpft.v7i1.2719.
Full textSopian, Herman. "Deskripsi Kemampuan Berpikir Logis dan Pemahaman Konsep Sistem Hormon pada Siswa Kelas XI SMA." Edubiologica Jurnal Penelitian Ilmu dan Pendidikan Biologi 7, no. 2 (December 28, 2019): 85. http://dx.doi.org/10.25134/edubiologica.v7i2.3023.
Full textTambunan, Janwar. "ANALISIS MODEL PEMBELAJARAN BLENDED LEARNING TERHADAP PEMAHAMAN DAN PENALARAN LOGIS MAHASISWA." Jurnal Suluh Pendidikan 9, no. 2 (September 29, 2021): 80–89. http://dx.doi.org/10.36655/jsp.v9i2.587.
Full textSartor, Giovanni. "The Logic of Proportionality: Reasoning with Non-Numerical Magnitudes." German Law Journal 14, no. 8 (August 1, 2013): 1419–56. http://dx.doi.org/10.1017/s2071832200002339.
Full textSyafitri, Rani, Zetra Hainul Putra, and Eddy Noviana. "Fifth Grade Students’ Logical Thinking in Mathematics." JOURNAL OF TEACHING AND LEARNING IN ELEMENTARY EDUCATION (JTLEE) 3, no. 2 (July 31, 2020): 157. http://dx.doi.org/10.33578/jtlee.v3i2.7840.
Full textM. H. Gedig and S. F. Stiemer. "Qualitative & Semi-Quantitative Reasoning Techniques for Engineering Projects at Conceptual Stage." Electronic Journal of Structural Engineering 3 (January 1, 2003): 67–88. http://dx.doi.org/10.56748/ejse.331.
Full textIbeling, Duligur, and Thomas Icard. "Probabilistic Reasoning Across the Causal Hierarchy." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 06 (April 3, 2020): 10170–77. http://dx.doi.org/10.1609/aaai.v34i06.6577.
Full textM. H. Gedig and S. F. Stiemer. "Computer Application to Study Engineering Projects at the Early Stages of Development." Electronic Journal of Structural Engineering 3 (January 1, 2003): 43–66. http://dx.doi.org/10.56748/ejse.330.
Full textNiu, Yue, Jonathan Sterling, Harrison Grodin, and Robert Harper. "A cost-aware logical framework." Proceedings of the ACM on Programming Languages 6, POPL (January 16, 2022): 1–31. http://dx.doi.org/10.1145/3498670.
Full textDissertations / Theses on the topic "Quantitative and logical reasoning"
Videla, Santiago. "Reasoning on the response of logical signaling networks with answer set programming." Phd thesis, Universität Potsdam, 2014. http://opus.kobv.de/ubp/volltexte/2014/7189/.
Full textDeciphering the functioning of biological networks is one of the central tasks in systems biology. In particular, signal transduction networks are crucial for the understanding of the cellular response to external and internal perturbations. Importantly, in order to cope with the complexity of these networks, mathematical and computational modeling is required. We propose a computational modeling framework in order to achieve more robust discoveries in the context of logical signaling networks. More precisely, we focus on modeling the response of logical signaling networks by means of automated reasoning using Answer Set Programming (ASP). ASP provides a declarative language for modeling various knowledge representation and reasoning problems. Moreover, available ASP solvers provide several reasoning modes for assessing the multitude of answer sets. Therefore, leveraging its rich modeling language and its highly efficient solving capacities, we use ASP to address three challenging problems in the context of logical signaling networks: learning of (Boolean) logical networks, experimental design, and identification of intervention strategies. Overall, the contribution of this thesis is three-fold. Firstly, we introduce a mathematical framework for characterizing and reasoning on the response of logical signaling networks. Secondly, we contribute to a growing list of successful applications of ASP in systems biology. Thirdly, we present a software providing a complete pipeline for automated reasoning on the response of logical signaling networks.
Dias, M. G. "Logical reasoning." Thesis, University of Oxford, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.233533.
Full textAndersson, Robin. "Implementation av ett kunskapsbas system för rough set theory med kvantitativa mätningar." Thesis, Linköping University, Department of Computer and Information Science, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1756.
Full textThis thesis presents the implementation of a knowledge base system for rough sets [Paw92]within the logic programming framework. The combination of rough set theory with logic programming is a novel approach. The presented implementation serves as a prototype system for the ideas presented in [VDM03a, VDM03b]. The system is available at "http://www.ida.liu.se/rkbs".
The presented language for describing knowledge in the rough knowledge base caters for implicit definition of rough sets by combining different regions (e.g. upper approximation, lower approximation, boundary) of other defined rough sets. The rough knowledge base system also provides methods for querying the knowledge base and methods for computing quantitative measures.
We test the implemented system on a medium sized application example to illustrate the usefulness of the system and the incorporated language. We also provide performance measurements of the system.
Leevers, Hilary Janet. "Children's logical reasoning." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362050.
Full textKouri, Teresa. "Logical Instrumentalism." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1472751856.
Full textCarbin, Michael (Michael James). "Logical reasoning for approximate and unreliable computation." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/99813.
Full textCataloged 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.
Romo, Maria Susanna 1968. "Cultural differences in memory and logical reasoning." Thesis, The University of Arizona, 1995. http://hdl.handle.net/10150/291706.
Full textRajaratnam, David Computer Science & 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.
Full textBennett, Brandon. "Logical representations for automated reasoning about spatial relationships." Thesis, University of Leeds, 1997. http://etheses.whiterose.ac.uk/1271/.
Full textCaruso, Matteo. "On logical quantitative methods in politics." Thesis, IMT Alti Studi Lucca, 2021. http://e-theses.imtlucca.it/337/1/Caruso_phdthesis.pdf.
Full textBooks on the topic "Quantitative and logical reasoning"
International Joint Conference on Qualitative and Quantitative Practical Reasoning (1st 1997 Bad Honnef, Germany). Qualitative and quantitative practical reasoning: First International Joint Conference on Qualitative and Quantitative Practical Reasoning, ECSQARU-FAPR '97 : Bad Honnef, Germany, June 9-12, 1997 : proceedings. Berlin: Springer, 1997.
Find full textCouncil, Law School Admission, and Law School Admission Services (U.S.), eds. Logical reasoning workbook. Newton, Pa: Law Services, 1990.
Find full textLiu, Weiru. Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 11th European Conference, ECSQARU 2011, Belfast, UK, June 29–July 1, 2011. Proceedings. Berlin, Heidelberg: Springer-Verlag GmbH Berlin Heidelberg, 2011.
Find full textClaudio, Sossai, and Chemello Gaetano, eds. Symbolic and quantitative approaches to reasoning with uncertainty: 10th European conference, ECSQARU 2009, Verona, Italy, July 1-3, 2009 ; proceedings. Berlin: Springer, 2009.
Find full text1956-, Allwein Gerard, and Barwise Jon, eds. Logical reasoning with diagrams. New York: Oxford University Press, 1996.
Find full textLogical reasoning in science & technology. Toronto: J. Wiley & Sons Canada, 1991.
Find full textF, Strawson P. Introduction to logical theory. London: Methuen, 1991.
Find full textWainman, Grant. Cognitive & logical consistency in syllogistic reasoning. Sudbury, Ont: Laurentian University, Department of Psychology, 1995.
Find full textKiersky, James Hugh. Thinking critically: Techniques for logical reasoning. Minneapolis/St. Paul: West Pub. Co., 1995.
Find full textLegal reasoning: Semantic and logical analysis. New York: P. Lang, 1985.
Find full textBook chapters on the topic "Quantitative and logical reasoning"
Finger, Marcelo. "Quantitative Logic Reasoning." In Trends in Logic, 241–71. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98797-2_12.
Full textDemolombe, Robert, Andrew J. I. Jones, and Jose Carmo. "Toward a uniform logical representation of different kinds of integrity constraints." In Qualitative and Quantitative Practical Reasoning, 614–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0035653.
Full textSaad, Emad. "A Logical Approach to Qualitative and Quantitative Reasoning." In Lecture Notes in Computer Science, 173–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-75256-1_18.
Full textWilson, Nic, and Jérôme Mengin. "Logical Deduction using the Local Computation Framework." In Symbolic and Quantitative Approaches to Reasoning and Uncertainty, 386–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48747-6_36.
Full textSlaney, John, and Robert Meyer. "Logic for two: The semantics of distributive substructural logics." In Qualitative and Quantitative Practical Reasoning, 554–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0035648.
Full textLoreti, Michele, and Aniqa Rehman. "A Logical Framework for Reasoning About Local and Global Properties of Collective Systems." In Quantitative Evaluation of Systems, 133–49. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16336-4_7.
Full textWeydert, Emil. "Rational Default Quantifier Logic." In Qualitative and Quantitative Practical Reasoning, 589–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0035651.
Full textBesnard, Philippe, Jean-Marc Guinnebault, and Emmanuel Mayer. "Propositional quantification for conditional logic." In Qualitative and Quantitative Practical Reasoning, 183–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0035622.
Full textHunter, Anthony. "Using default logic for lexical knowledge." In Qualitative and Quantitative Practical Reasoning, 322–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0035632.
Full textKern-Isberner, Gabriele. "A logically sound method for uncertain reasoning with quantified conditionals." In Qualitative and Quantitative Practical Reasoning, 365–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0035635.
Full textConference papers on the topic "Quantitative and logical reasoning"
Mardare, Radu, Prakash Panangaden, and Gordon Plotkin. "Quantitative Algebraic Reasoning." In LICS '16: 31st Annual ACM/IEEE Symposium on Logic in Computer Science. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2933575.2934518.
Full textMaubert, Bastien, Munyque Mittelmann, Aniello Murano, and Laurent Perrussel. "Strategic Reasoning in Automated Mechanism Design." In 18th International Conference on Principles of Knowledge Representation and Reasoning {KR-2021}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/kr.2021/46.
Full textHoffmann, Jan, Michael Marmar, and Zhong Shao. "Quantitative Reasoning for Proving Lock-Freedom." In 2013 Twenty-Eighth Annual IEEE/ACM Symposium on Logic in Computer Science (LICS 2013). IEEE, 2013. http://dx.doi.org/10.1109/lics.2013.18.
Full textBouyer, Patricia, Orna Kupferman, Nicolas Markey, Bastien Maubert, Aniello Murano, and Giuseppe Perelli. "Reasoning about Quality and Fuzziness of Strategic Behaviours." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/220.
Full textMio, Matteo, Ralph Sarkis, and Valeria Vignudelli. "Beyond Nonexpansive Operations in Quantitative Algebraic Reasoning." In LICS '22: 37th Annual ACM/IEEE Symposium on Logic in Computer Science. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3531130.3533366.
Full textHecher, Markus, Yasir Mahmood, Arne Meier, and Johannes Schmidt. "Quantitative Claim-Centric Reasoning in Logic-Based Argumentation." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. California: International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/377.
Full textGavazzo, Francesco. "Quantitative Behavioural Reasoning for Higher-order Effectful Programs." In LICS '18: 33rd Annual ACM/IEEE Symposium on Logic in Computer Science. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3209108.3209149.
Full textBesin, Viktor, Markus Hecher, and Stefan Woltran. "Utilizing Treewidth for Quantitative Reasoning on Epistemic Logic Programs (Extended Abstract)." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/732.
Full textChowdhury, Ahmed, Lakshmi N. A. Venkatanarasimhan, and Chiradeep Sen. "A Formal Representation of Conjugate Verbs in Function Modeling." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22630.
Full textCharalambidis, Angelos, George Papadimitriou, Panos Rondogiannis, and Antonis Troumpoukis. "A Many-valued Logic for Lexicographic Preference Representation." In 18th International Conference on Principles of Knowledge Representation and Reasoning {KR-2021}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/kr.2021/62.
Full textReports on the topic "Quantitative and logical reasoning"
Driesen, Jacob. Differential Effects of Visual and Auditory Presentation on Logical Reasoning. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2546.
Full textVarela, Carlos A. Stochastic Quantitative Reasoning for Autonomous Mission Planning. Fort Belvoir, VA: Defense Technical Information Center, April 2014. http://dx.doi.org/10.21236/ada599522.
Full textLutz, Carsten. NExpTime-complete Description Logics with Concrete Domains. Aachen University of Technology, 1999. http://dx.doi.org/10.25368/2022.104.
Full textLutz, Carsten. TheComplexity of Reasoning with Concrete Domains (Revised Version). Aachen University of Technology, 1999. http://dx.doi.org/10.25368/2022.88.
Full textAhn, Ki Yung. The Nax Language: Unifying Functional Programming and Logical Reasoning in a Language based on Mendler-style Recursion Schemes and Term-indexed Types. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2086.
Full textBorgwardt, Stefan, Marco Cerami, and Rafael Peñaloza. Subsumption in Finitely Valued Fuzzy EL. Technische Universität Dresden, 2015. http://dx.doi.org/10.25368/2022.212.
Full textTámola, Alejandro, and María Carmen Fernández Díez. Initial Conditions for Economic Recovery after COVID-19: A Logical and Quantitative Framework for Latin American and Caribbean Countries. Inter-American Development Bank, August 2020. http://dx.doi.org/10.18235/0002628.
Full textLutz, Carsten, Carlos Areces, Ian Horrocks, and Ulrike Sattler. Keys, Nominals, and Concrete Domains. Technische Universität Dresden, 2002. http://dx.doi.org/10.25368/2022.122.
Full textCamilo, Cláudia, Andréia Salmazo, Margari da Vaz Garrido, and Maria Manuela Calheiros. Parents’ executive functioning in parenting outcomes: A meta-analytic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, March 2023. http://dx.doi.org/10.37766/inplasy2023.3.0067.
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