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Relevant bibliographies by topics / Conceptual reasoning

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Academic literature on the topic 'Conceptual reasoning'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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Journal articles on the topic "Conceptual reasoning"

1

Dantlgraber, Michael, Tim Kuhlmann, and Ulf-Dietrich Reips. "Conceptual fluency in inductive reasoning." PLOS ONE 14, no. 11 (November 21, 2019): e0225050. http://dx.doi.org/10.1371/journal.pone.0225050.

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Gerken, Mikkel. "Conceptual Equivocation and Warrant by Reasoning." Australasian Journal of Philosophy 89, no. 3 (September 2011): 381–400. http://dx.doi.org/10.1080/00048402.2010.488267.

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Bergamaschi, Sonia, and Claudio Sartori. "On taxonomic reasoning in conceptual design." ACM Transactions on Database Systems 17, no. 3 (September 1992): 385–422. http://dx.doi.org/10.1145/132271.132272.

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Welch, Richard V., and John R. Dixon. "Guiding conceptual design through behavioral reasoning." Research in Engineering Design 6, no. 3 (September 1994): 169–88. http://dx.doi.org/10.1007/bf01607277.

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Hung, Woei, and David H. Jonassen. "Conceptual Understanding of Causal Reasoning in Physics." International Journal of Science Education 28, no. 13 (October 27, 2006): 1601–21. http://dx.doi.org/10.1080/09500690600560902.

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Cyre, W. R. "Conceptual representation of waveforms for temporal reasoning." IEEE Transactions on Computers 43, no. 2 (1994): 186–200. http://dx.doi.org/10.1109/12.262123.

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Hacid, M. S., J. M. Petit, and F. Toumani. "Representing and Reasoning on Database Conceptual Schemas." Knowledge and Information Systems 3, no. 1 (February 2001): 52–80. http://dx.doi.org/10.1007/pl00011659.

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Nilsson, Per. "Conceptual variation and coordination in probability reasoning." Journal of Mathematical Behavior 28, no. 4 (December 2009): 247–61. http://dx.doi.org/10.1016/j.jmathb.2009.10.003.

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Houser, Nathan. "Peirce on Practical Reasoning." American Journal of Semiotics 36, no. 1 (2020): 117–34. http://dx.doi.org/10.5840/ajs202082763.

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It is generally agreed that what distinguishes practical reasoning from more thoughtful reasoning is that practical reasoning properly results in action rather than in conceptual conclusions. There is much disagreement, however, about how appropriate actions follow from practical reasoning and it is commonly supposed that the connection between reasoning and action can neither be truly inferential nor strictly causal. Peirce appears to challenge this common assumption. Although he would agree that conscious and deliberate argumentation results in conceptual conclusions (mental states) rather than directly in practical action, his extended semiotic account of mental activity allows for unconscious (instinctive or habitual) cognitive processing which, though inferential, genuinely concludes in action rather than in conceptual states (logical interpretants). Peirce acknowledges that for practical reasoning to properly conclude in action it is necessary for final (semiotic) causation to operate in conjunction with efficient causation, although how this can be explained remains problematic. Still, his account is rich and promising and has much to contribute to contemporary research on practical reasoning.

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Tselishchev, Vitaly V. "Mathematical Reasoning." Epistemology & Philosophy of Science 57, no. 4 (2020): 74–86. http://dx.doi.org/10.5840/eps202057459.

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The article is devoted to the comparison of two types of proofs in mathematical practice, the methodological differences of which go back to the difference in the understanding of the nature of mathematics by Descartes and Leibniz. In modern philosophy of mathematics, we talk about conceptual and formal proofs in connection with the so-called Hilbert Thesis, according to which every proof can be transformed into a logical conclusion in a suitable formal system. The analysis of the arguments of the proponents and opponents of the Thesis, “conceptualists” and “formalists”, is presented respectively by the two main antagonists – Y. Rav and J. Azzouni. The focus is on the possibility of reproducing the proof of “interesting” mathematical theorems in the form of a strict logical conclusion, in principle feasible by a mechanical procedure. The argument of conceptualists is based on pointing out the importance of other aspects of the proof besides the logical conclusion, namely, in introducing new concepts, methods, and establishing connections between different sections of meaningful mathematics, which is often illustrated by the case of proving Fermat’s Last Theorem (Y. Rav). Formalists say that a conceptual proof “points” to the formal logical structure of the proof (J. Azzouni). The article shows that the disagreement is based on the assumption of asymmetry of mutual translation of syntactic and semantic structures of the language, as a result of which the formal proof loses important semantic factors of proof. In favor of a formal proof, the program of univalent foundations of mathematics In. Vojevodski, according to which the future of mathematical proofs is associated with the availability of computer verification programs. In favor of conceptual proofs, it is stated (A. Pelc) that the number of steps in the supposed formal logical conclusion when proving an “interesting” theorem exceeds the cognitive abilities of a person. The latter circumstance leads the controversy beyond the actual topic of mathematical proof into the epistemological sphere of discussions of “mentalists” and “mechanists” on the question of the supposed superiority of human intelligence over the machine, initiated by R. Penrose in his interpretation of the Second Theorem of Goedel, among whose supporters, as it turned out, was Goedel himself.

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Dissertations / Theses on the topic "Conceptual reasoning"

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Nowak, Krzysztof Zbigniew. "Conceptual reasoning : belief, multiple agents and preference /." Title page, table of contents and abstract only, 1998. http://web4.library.adelaide.edu.au/theses/09PH/09phn946.pdf.

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Degirmenci, Yilmaz. "Reasoning by analogy using holographic conceptual projection." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2002. http://library.nps.navy.mil/uhtbin/hyperion-image/02sep%5FDegirmenci.pdf.

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Meisel, Helmut. "Ontology representation and reasoning : a conceptual level approach." Thesis, University of Aberdeen, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.420216.

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Ontologies play a key role in many areas of Computing Science, such as Information Retrieval, Knowledge Management, and Knowledge Engineering. However, Ontology development and maintenance is a challenging task that is currently not very well supported by software tools. Most existing ontology editors cannot provide the kind of automated reasoning support that is required for the verification and for the validation of ontologies. More concretely, such an automated support should (i) check the ontology consistency and (ii) suggest possible enhancements to the ontology taxonomy. Description Logic engines compute the kind of inferences that are useful for an automated ontology verification and validation but are not suitable for all ontology representation languages. More concretely, the semantics of Description Logics is based on the Open World Assumption, whereas the semantics of some ontology representation languages is based on the Closed World Assumption. Furthermore, the knowledge model of Description Logics is derived from Frame-based knowledge representation. Therefore Description Logics lack some modelling primitives necessary to express knowledge that can be represented with conceptual modelling languages. On the other hand, conceptual modelling languages (i) do not have the same expressive power as Frame-based ontology languages and (ii) no reasoners are available for automated reasoning with these languages. Hence, this thesis introduces the Conceptual Knowledge Modelling Language (CKML) and proposes an approach for the verification and validation of CKML ontologies. Rather than developing a special-purpose reasoning algorithm for CKML, we investigate how Description Logic engines can be used for this task. This approach can also be applied to a language that describes database schemas specified with the Enhanced Entity-Relationship model.

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Croitoru, Madalina. "Conceptual graphs at work : efficient reasoning and applications." Thesis, University of Aberdeen, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.439993.

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This thesis describes original research in the field of knowledge representation and reasoning by presenting novel extensions to the Conceptual Graph formalism which increase their reasoning capabilities and conceptual modelling applicability in Artificial Intelligence. Conceptual Graphs benefit from graph-based reasoning mechanisms, plug-in capabilities over existing data structures and good visualization capabilities. These advantages have to be adapted for an information era where quick results and representation versatility are essential for successful frameworks. This thesis will show how to extend Conceptual Graphs as a knowledge representation and reasoning formalism to address these needs. We claim that this extension has to focus on both semantic and syntactic aspects. More precisely we improve existing reasoning algorithms and propose Conceptual Graphs extensions that allow for the representation of hierarchical knowledge and concurrent, interrelated events. Our work is evaluated theoretically. We highlight new polynomial instances for the NP-complete problem of projection checking (the main reasoning mechanism for Conceptual Graphs). We demonstrate the soundness and completeness of our proposed extensions. We show how our extensions can be successfully employed for conceptual modelling.

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Banerjee, S. "Conceptual structures in experience bases and analogical reasoning." Thesis, University of Bristol, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.279797.

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Brown, Kenneth N. "Conceptual geometric reasoning in artificial intelligence and engineering." Thesis, University of Bristol, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337201.

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Flanagan, Gregory M. "Conceptual Requirement Validation for Architecture Design Systems." DigitalCommons@CalPoly, 2011. https://digitalcommons.calpoly.edu/theses/653.

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Computer-aided architectural design (CAAD) programs represent architectural design at a low level of spatial abstraction. While this representation model allows CAAD programs to capture the precise spatial characteristics of a design, it means that CAAD programs lack the underlying computational apparatus necessary to reason about design at a conceptual level. This thesis is a first step towards building a framework that bridges the gap between the conceptual aspects of a design and its low level CAAD-based spatial representation. Specifically, this thesis presents a new framework, referred to as the Conceptual Requirements Reasoner (CRR), which provides an architect with a framework to validate conceptual design requirements. The CRR will demonstrate how qualitative spatial representation and reasoning techniques can be used as the link between a design's conceptual requirements and its underlying quantitative spatial representation. A museum case study is presented to demonstrate the application of the CRR in a real world design context. It introduces a set of museum design requirements identified in research and shows how these requirements can be validated using the CRR. The results of the case study shows that the CRR is an effective tool for conceptual requirements reasoning.

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Vinney, John Edward. "Function based techniques for assisting engineering conceptual design." Thesis, University of the West of England, Bristol, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.387937.

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The basic concept of this work is that functional modelling techniques are applicable to and of practical use in, producing a qualitative model of conceptual engineering design. A qualitative function based model of conceptual design has been developed and a computer based implementation has been built and tested. The rationale behind the modelling scheme and the computer implementation are described in detail. In addition to a review of existing models of design the research provides a significant new capability in four main areas: • An ability to generate new concepts with a controlled degree of similarity to existing designs. • A new function based model of engineering conceptual design. • The COncept Design ASsistant (CODAS) system, a computer based implementation of the function based model, has been developed and tested. • A new symbolic representation language. CODAS is a hybrid case-based and function-based modelling system, implemented in the domain of mechanical device design, which demonstrates the practical application of this new model. The CODAS system aims to provide a design support tool which can invent both routine and novel devices based on experience gained from past successful design solutions. Fast and efficient data handling is achieved by utilizing Case Based Reasoning (CBR) technology to store and retrieve past design solutions which are defined in terms of a symbolic representation language. The underlying design model is function based and employs a technique of divergent function to form mapping to produce physical embodiments of the proposed functional solutions.

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Kahn, Sami. "A Conceptual Analysis of Perspective Taking in Support of Socioscientific Reasoning." Scholar Commons, 2015. https://scholarcommons.usf.edu/etd/5513.

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Scientific literacy is concerned with the informed citizens' ability to negotiate scientifically-related societal issues. The suite of skills necessary to negotiate these complex issues is referred to as Socioscientific Reasoning (SSR). SSR requires, among other things, perspective-taking abilities in order to consider the multi-faceted nature of these open-ended, debatable socioscientific issues (SSI). Developing interventions and instruments to foster and measure perspective taking in support of SSR is therefore critical to the promotion of functional scientific literacy through both research and practice. Although widely studied in many disciplines, perspective taking is a particularly tangled construct that has been used to describe a range of activities representing different psychological domains and applied interchangeably with related constructs such as role taking, empathy, and theory of mind. This ambiguity makes it difficult to ensure construct validity and prevents science education researchers from honing in on the precise skills they wish to study and promote. To clarify the construct of perspective taking, this study undertook a conceptual analysis to operationalize perspective taking, drawing comparisons and distinctions between it and related constructs. Further, by applying a method known as conception development, perspective taking was positioned in the context of SSR, particularly as it relates to moral development, in order to devise a more precise construct relating perspective taking to SSR called socioscientific perspective taking (SSPT). It is asserted that SSPT requires engagement with others or their circumstances, an etic/emic shift, and a moral context comprised of reflective and reflexive judgment. Finally, in order to identify promising interventions for promoting SSPT in the science classroom, the newly-developed SSPT construct was applied to a series of extensively researched curricular frameworks that promote perspective taking in three non-science disciplines including historical empathy (social studies education), method acting (theater education), and autism intervention (special education). The aim of this theoretical inquiry was to translate successful perspective-taking interventions into SSI contexts, yielding an array of promising approaches for fostering SSPT while assessing the feasibility of each of these fields as potential sources for novel and expansive work in SSI to promote scientific literacy. Implications for science education research and practice are discussed.

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Jensen, Jessica L. "Teachers' use of reasoning-based questions in procedural and conceptual lessons." Diss., University of Iowa, 2017. https://ir.uiowa.edu/etd/5522.

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Recent research shows that teachers’ level of Mathematical Knowledge for Teaching (MKT) and their beliefs about teaching and learning effect teaching practices and student achievement. Higher levels of MKT typically lead to more effective teaching abilities in terms of helping students make meaning of mathematical concepts, but beliefs seem to be a mediating factor in this relationship. One specific teaching practice that can help guide students through this meaning making is questioning. Although it is known that MKT and beliefs play an important role in outcomes of teacher practices, the effects of these factors on teachers’ ability to ask meaningful questions have not yet been explored. This mixed methods study uses descriptive data of teachers’ questioning patterns with a cross-case analysis of five elementary mathematics teachers to investigate how the nature of elementary teachers’ questioning changes between procedural and conceptual mathematics lessons, and how teachers’ level of MKT and their beliefs about teaching and learning aid in or inhibit their ability to ask questions that engage students in mathematical reasoning and sense making. High levels of alignment with rule-based beliefs about teaching mathematics were found to be a major inhibitor to teachers’ ability to ask meaningful questions in the classroom. While high MKT is helpful in creating reasoning-based dialogue in the classroom, high rule-based beliefs limit the potential effects of high MKT on teacher questioning practices. Relationships between MKT, beliefs, and questioning are further dissected, and implications for teacher development efforts are discussed.

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Books on the topic "Conceptual reasoning"

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Corbett, Dan. Reasoning and unification over conceptual graphs. New York: Kluwer Academic/Plenum Publishers, 2003.

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Corbett, Dan. Reasoning and Unification over Conceptual Graphs. Boston, MA: Springer US, 2003.

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Corbett, Dan. Reasoning and Unification over Conceptual Graphs. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0087-2.

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Eklund, Peter, and Ollivier Haemmerlé, eds. Conceptual Structures: Knowledge Visualization and Reasoning. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-70596-3.

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Vaidya, Anand. Logic & critical reasoning: Conceptual foundations and techniques of evaluation. Dubuque, IA: Kendall Hunt, 2011.

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1962-, Eklund Peter W., Haemmerlé Ollivier, Siekmann Jörg H, and SpringerLink (Online service), eds. Conceptual Structures: Knowledge Visualization and Reasoning: 16th International Conference on Conceptual Structures, ICCS 2008 Toulouse, France, July 7-11, 2008 Proceedings. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2008.

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Cao, Tru. Conceptual graphs and fuzzy logic: A fusion for representing and reasoning with linguistic information. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.

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Wahl, Claes. The state of statistics: Conceptual change and statistical reasoning in the modern state, 1870-1940. Stockholm: Dept. of Political Science, University of Stockholm, 1996.

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Rute Elizabete de Souza Rosa Borba. The effect of number meanings, conceptual invariants and symbolic representations on children's reasoning about directed numbers. Oxford: Oxford Brookes University, 2002.

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Wohlgenannt, Gerhard. Learning ontology relations by combining corpus-based techniques and reasoning on data from semantic web sources. Frankfurt am Main: P. Lang, 2011.

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Book chapters on the topic "Conceptual reasoning"

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Andreasen, Mogens Myrup, Claus Thorp Hansen, and Philip Cash. "Function Reasoning." In Conceptual Design, 267–305. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19839-2_11.

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Andreasen, Mogens Myrup, Claus Thorp Hansen, and Philip Cash. "Property Reasoning." In Conceptual Design, 307–40. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19839-2_12.

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Andreasen, Mogens Myrup, Claus Thorp Hansen, and Philip Cash. "Dispositional Reasoning." In Conceptual Design, 341–68. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19839-2_13.

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Siena, Alberto, Silvia Ingolfo, Anna Perini, Angelo Susi, and John Mylopoulos. "Automated Reasoning for Regulatory Compliance." In Conceptual Modeling, 47–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41924-9_5.

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Barwise, Jon. "Heterogeneous reasoning." In Conceptual Graphs for Knowledge Representation, 64–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-56979-0_3.

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Liaskos, Sotirios, Shakil M. Khan, Mikhail Soutchanski, and John Mylopoulos. "Modeling and Reasoning with Decision-Theoretic Goals." In Conceptual Modeling, 19–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41924-9_3.

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Priss, Uta. "A Semiotic-Conceptual Analysis of Conceptual Learning." In Graph-Based Representation and Reasoning, 122–36. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40985-6_10.

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Giorgini, Paolo, John Mylopoulos, Eleonora Nicchiarelli, and Roberto Sebastiani. "Reasoning with Goal Models." In Conceptual Modeling — ER 2002, 167–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45816-6_22.

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von Tetzchner, Stephen. "Conceptual Development and Reasoning." In Child and Adolescent Psychology, 217–39. 1 Edition. | New York : Routledge, 2019.: Routledge, 2018. http://dx.doi.org/10.4324/9781315742113-12.

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Thornton, Stephanie. "Reasoning and Conceptual Understanding." In Understanding Human Development, 218–64. London: Macmillan Education UK, 2008. http://dx.doi.org/10.1007/978-1-137-29449-4_6.

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Conference papers on the topic "Conceptual reasoning"

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Calvanese, D., G. De Giacomo, M. Lenzerini, D. Nardi, and R. Rosati. "Information integration: conceptual modeling and reasoning support." In Proceedings 3rd IFCIS International Conference on Cooperative Information Systems (Cat No 98EX122) COOPIS-98. IEEE, 1998. http://dx.doi.org/10.1109/coopis.1998.706234.

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Rickard, John T., Janet Aisbett, and Greg Gibbon. "Knowledge Representation and Reasoning in Conceptual Spaces." In 2007 IEEE Symposium on Foundations of Computational Intelligence. IEEE, 2007. http://dx.doi.org/10.1109/foci.2007.371531.

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Xiaodong Wang and Shizhong Liao. "Constructing conceptual neighborhood for reasoning about motion." In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccasm.2010.5622709.

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Combi, Carlo, Matteo Gozzi, Jose M. Juarez, Barbara Oliboni, and Giuseppe Pozzi. "Conceptual Modeling of Temporal Clinical Workflows." In 14th International Symposium on Temporal Representation and Reasoning (TIME'07). IEEE, 2007. http://dx.doi.org/10.1109/time.2007.45.

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Han, Jiaxin. "Conceptual Space and Reasoning Method of Intelligent System." In 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery. IEEE, 2009. http://dx.doi.org/10.1109/fskd.2009.212.

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Artale, A. "Reasoning on temporal conceptual schemas with dynamic constraints." In Proceedings. 11th International Symposium on Temporal Representation and Reasoning, 2004. TIME 2004. IEEE, 2004. http://dx.doi.org/10.1109/time.2004.1314423.

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Sun, J., D. K. Kalenchuk, D. Xue, and P. Gu. "Neural Network-Based Fuzzy Reasoning for Conceptual Design Evaluation." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/dac-8559.

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Abstract This paper presents a neural network-based fuzzy reasoning method for design candidate evaluation and identification to improve design quality and efficiency at the crucial conceptual design stage. The evaluation and identification of design candidates are carried out through the following four steps: (1) acquisition of customer needs and ranking of their importance, (2) establishment of measurable metrics and their relations with customer needs, (3) development of design specifications and initial evaluation of design candidates, and (4) evaluation and identification of design candidates based on design specifications and customer needs. A case study is given to show the effectiveness of the neural network-based fuzzy reasoning method in conceptual design evaluation.

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Orponen, P., P. Floreen, P. Myllymaki, and H. Tirri. "A neural implementation of conceptual hierarchies with Bayesian reasoning." In 1990 IJCNN International Joint Conference on Neural Networks. IEEE, 1990. http://dx.doi.org/10.1109/ijcnn.1990.137585.

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Kalathur, Suresh. "Defeasible reasoning with conceptual graphs (abstract and references only)." In the 19th annual conference. New York, New York, USA: ACM Press, 1991. http://dx.doi.org/10.1145/327164.328832.

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Pyper, Brian A., N. Sanjay Rebello, Paula V. Engelhardt, and Chandralekha Singh. "Changing scientific reasoning and conceptual understanding in college students." In 2011 PHYSICS EDUCATION RESEARCH CONFERENCE. AIP, 2012. http://dx.doi.org/10.1063/1.3679994.

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