Готові списки джерел за темами / Reasoning

Добірка наукової літератури з теми "Reasoning"

Автор: Grafiati
Опубліковано: 4 червня 2021
Оновлено: 29 липня 2024

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Статті в журналах з теми "Reasoning"

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Bremner, Andrew J., and Denis Mareschal. "Reasoning . . . what reasoning?" Developmental Science 7, no. 4 (September 2004): 419–21. http://dx.doi.org/10.1111/j.1467-7687.2004.00360.x.

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2

Foos, Paul W. "Reasoning About Reasoning." Contemporary Psychology: A Journal of Reviews 41, no. 9 (September 1996): 917–18. http://dx.doi.org/10.1037/003142.

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3

Mata, André, Klaus Fiedler, Mário B. Ferreira, and Tiago Almeida. "Reasoning about others' reasoning." Journal of Experimental Social Psychology 49, no. 3 (May 2013): 486–91. http://dx.doi.org/10.1016/j.jesp.2013.01.010.

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4

Alaoui, Larbi, Katharina A. Janezic, and Antonio Penta. "Reasoning about others' reasoning." Journal of Economic Theory 189 (September 2020): 105091. http://dx.doi.org/10.1016/j.jet.2020.105091.

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5

Hafizallah, Yandi. "Pemikiran Abed Al-Jabiri Terhadap Nalar Arab." MAWA'IZH: JURNAL DAKWAH DAN PENGEMBANGAN SOSIAL KEMANUSIAAN 10, no. 1 (July 18, 2019): 60–76. http://dx.doi.org/10.32923/maw.v10i1.742.

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This paper aims to explain and analyze the epistemological aspects based on the thoughts of Abed al-Jabiri, especially regarding the thinking of three Arabic reasoning of al-Jabiri. The study refers to three thoughts of Arabic al-Jabiri reasoning about epistemology namely: "epistemology of Bayani", the epistemology of Irfani ", and" epistemology of Burhani". The search for the texts relating to the three epistemologies produces several findings in this study, among others: 1) Relevance between three Arabic reasoning that does not always stand alone but all three reasoning are also integrated with each other, even though Arabic reasoning is a formation from a culture; 2) The shift of reasoning culture analyzed using the socio-historical approach to the development of Arabic reasoning makes Jabiri make Arabic reasoning a "thinking structure", each of which has advantages and disadvantages; 3) The criticisms of the reasoning model conducted by Abed al-Jabiri are used to formulate methods of understanding knowledge. The three Arabic reasonings described by abed al-Jabiri rely on aspects emphasized in reason and reality, philosophy and science, and revelation texts and Nash.
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6

NAKAJIMA, Nobuyuki. "Inference, Reasoning, and Fuzzy Reasoning." Journal of Japan Society for Fuzzy Theory and Systems 6, no. 6 (1994): 1105–14. http://dx.doi.org/10.3156/jfuzzy.6.6_1105.

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7

Rice, Hugh. "IV—Practical Reasoning as Reasoning." Proceedings of the Aristotelian Society 89, no. 1 (June 1, 1989): 49–64. http://dx.doi.org/10.1093/aristotelian/89.1.49.

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8

Cave, Peter. "Reeling and A-Reasoning: Surprise Examinations and Newcomb's Tale." Philosophy 79, no. 4 (October 2004): 609–16. http://dx.doi.org/10.1017/s0031819104000476.

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Certain paradoxes set us reeling endlessly. In surprise examination paradoxes, pupils' reasonings lead them to reel between expecting an examination and expecting none. With Newcomb's puzzle, choosers reel between reasoning in favour of choosing just one box and choosing two. The paradoxes demand an answer to what it is rational to believe or do. Highlighting other reelings and puzzles, this paper shows that the paradoxes should come as no surprise. The paradoxes demand an end to our reasoning when the conditions they set ensure no end. They equivocate between, so to speak, reasoning in heaven and reasoning on earth; and, on the conditions set, not even an infinite god could reach a conclusion.
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Grusenmeyer, Corinne, and Alain Trognon. "Structures of natural reasoning within functional dialogues." Pragmatics and Cognition 4, no. 2 (January 1, 1996): 305–46. http://dx.doi.org/10.1075/pc.4.2.06gru.

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The aim of this paper is to describe and characterize some structural features of natural reasoning by analyzing a number of conversations held by operators during shift changeovers. During this work phase the operators have to cooperate in order to carry out the same process. This need to cooperate leads to dialogues and joint elaboration of information, especially when involving the reporting of a malfunction. Three dialogues observed at this work phase on two study sites (a paper mill and a nuclear power plant) are analyzed. These analyses show that the step by step follow-up of the operators' collective reasoning is feasible. They highlight that these reasonings are complex experimental and hypothetico-deductive reasonings. They are reasonings for action, that are elaborated as the conversation unfolds, and for which the operators do not always have the means of testing their hypotheses.
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10

Rips, L. J. "Reasoning." Annual Review of Psychology 41, no. 1 (January 1990): 321–53. http://dx.doi.org/10.1146/annurev.ps.41.020190.001541.

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Дисертації з теми "Reasoning"

1

Lin, Hanti. "Propositional Reasoning that Tracks Probabilistic Reasoning." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/399.

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Bayesians model one’s doxastic state by subjective probabilities. But in traditional epistemology, in logic-based artificial intelligence, and in everyday life, one’s doxastic state is usually expressed in a qualitative, binary way: either one accepts (believes) a proposition or one does not. What is the relationship between qualitative and probabilistic belief? I show that, besides the familiar lottery paradox (Kyburg 1961), there are two new, diachronic paradoxes that are more serious. A solution to the paradoxes, old and new, is provided by means of a new account of the relationship between qualitative and probabilistic belief. I propose that propositional beliefs should crudely but aptly represent one’s probabilistic credences. Aptness should include responses to new information so that propositional belief revision tracks Bayesian conditioning: if belief state B aptly represents degrees of belief p then the revised belief state K∗E should aptly represent the conditional degrees of belief p(·|E). I explain how to characterize synchronic aptness and qualitative belief revision to ensure the tracking property in the sense just defined. I also show that the tracking property is impossible if acceptance is based on thresholds or if qualitative belief revision is based on the familiar AGM belief revision theory of Alchourr ́on, G ̈ardenfors, and Makinson (1985).
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Chong, Waiyian. "Reflective reasoning." College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/3709.

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Анотація:
Thesis (Ph. D.) -- University of Maryland, College Park, 2006.
Thesis research directed by: Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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3

Dias, M. G. "Logical reasoning." Thesis, University of Oxford, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.233533.

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McGreggor, Brian Keith. "Fractal reasoning." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50337.

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Humans are experts at understanding what they see. Similarity and analogy play a significant role in making sense of the visual world by forming analogies to similar images encountered previously. Yet, while these acts of visual reasoning may be commonplace, the processes of visual analogy are not yet well understood. In this dissertation, I investigate the utility of representing visual information in a fractal manner for computing visual similarity and analogy. In particular, I develop a computational technique of fractal reasoning for addressing problems of visual similarity and novelty. I illustrate the effectiveness of fractal reasoning on problems of visual similarity and analogy on the Raven’s Progressive Matrices and Miller’s Analogies tests of intelligence, problems of visual novelty and oddity on the Odd One Out test of intelligence, and problems of visual similarity and oddity on the Dehaene test of core geometric reasoning. I show that the performance of my computational model on these various tests is comparable to human performance. Fractal reasoning provides a new method for computing answers to such problems. Specifically, I show that the choice of the level of abstraction of problem representation determines the degree to which an answer may be regarded as confident, and that that choice of abstraction may be controlled automatically by the algorithm as a means of seeking that confident answer. This emergence of ambiguity and its remedy via problem re-representation is afforded by the fractal representation. I also show how reasoning over sparse data (at coarse levels of abstraction) or homogeneous data (at finest levels of abstraction) could both drive the automatic exclusion of certain levels of abstraction, as well as provide a signal to shift the analogical reasoning from consideration of simple analogies (such as analogies between pairs of objects) to more complex analogies (such as analogies among triplets, or larger groups of objects). My dissertation also explores fractal reasoning in perception, including both biologically-inspired imprinting and bistable perception. In particular, it provides a computational explanation of bistable perception in the famous Necker cube problem that is directly tied to the process of determining a confident interpretation via re-representation. Thus, my research makes two primary contributions to AI theories of visual similarity and analogy. The first contribution is the Extended Analogy By Recall (ABR*) algorithm, the computational technique for visual reasoning that automatically adjusts fractal representations to an appropriate level of abstraction. The second contribution is the fractal representation itself, a knowledge representation that add the notion of self-similarity and re-representation to analogy making.
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Falcão, Renato Pinto de Queiroz. "Reasoning Maps." Florianópolis, SC, 2003. http://repositorio.ufsc.br/xmlui/handle/123456789/84814.

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Анотація:
Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia de Produção.
Made available in DSpace on 2012-10-20T12:45:01Z (GMT). No. of bitstreams: 1 225064.pdf: 1186448 bytes, checksum: 0c2e5acf545c7274024a1ada8d2abeb0 (MD5)
Esta dissertação apresenta uma ferramenta de apoio à decisão, baseada na Metodologia Multicritérios de Apoio à Decisão - MCDA, através do desenvolvimento de um software denominado Reasoning Maps. O software permite, de maneira integrada, a construção de mapas cognitivos, suas diversas análises topológicas e o cadastramento e análise de alternativas. Aborda um estudo de caso procurando demonstrar os recursos utilizados na criação, inicialmente, de um mapa cognitivo conciso, os diversos tipos de análises topológicas - caminhos, clusters e análise concisa, que corresponde à análise das causalidades entre conceitos do mapa. Evidencia a transformação do mapa conciso em um mapa difuso através da modelização dos graus de influência percebida pelo tomador de decisão. Procede com a entrada de medidores de performance (descritores), utilizados como parâmetro de avaliação de alternativas. Elabora o cadastro e a análise das alternativas utilizando os operadores fuzzy: Máximo, Média Ponderada, Mediana e Agregação Linear como suporte para efetivação dos cálculos. Gera relatórios das análises em tela e impressos. Permite ao decisor conhecer melhor o ambiente decisório e melhorar o nível de avaliação das alternativas. Formula conclusões e faz sugestões visando o aperfeiçoamento do estudo, no encerramento do texto. Um estudo de caso foi empregado para teste do software em uma situação real de apoio à decisão e é também descrito ao longo da dissertação.
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6

Etherington, David William. "Reasoning with incomplete information : investigations of non-monotonic reasoning." Thesis, University of British Columbia, 1986. http://hdl.handle.net/2429/27070.

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Анотація:
Intelligent behaviour relies heavily on the ability to reason in the absence of complete information. Until recently, there has been little work done on developing a formal understanding of how such reasoning can be performed. We focus on two aspects of this problem: default or prototypical reasoning, and closed-world or circumscriptive reasoning. After surveying the work in the field, we concentrate on Reiter's default logic and the various circumscriptive formalisms developed by McCarthy and others. Taking a largely semantic approach, we develop and/or extend model-theoretic semantics for the formalisms in question. These and other tools are then used to chart the capabilities, limitations, and interrelationships of the various approaches. It is argued that the formal systems considered, while interesting in their own rights, have an important role as specification/evaluation tools vis-a-vis explicitly computational approaches. An application of these principles is given in the formalization of inheritance networks in the presence of exceptions, using default logic.
Science, Faculty of
Computer Science, Department of
Graduate
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7

Simina, Marin. "Enterprise-directed reasoning : opportunism and deliberation in creative reasoning." Diss., Georgia Institute of Technology, 1999. http://hdl.handle.net/1853/9149.

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Ferdinandova, Ivana. "Models of Reasoning." Doctoral thesis, Universitat Autònoma de Barcelona, 2004. http://hdl.handle.net/10803/4044.

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Esta tesis estudia la aplicación de modelos de racionamiento humano en la área de la economía. El objetivo del análisis es observar el efecto que tienen distintos modelos de adaptación y aprendizaje sobre el resultado final de varios juegos.
En los tres trabajos que forman la tesis se analizan distintos juegos.
En el primero el juego es el Dilema del Prisionero y el objetivo es estudiar la influencia del aprendizaje social e individual o imitación sobre el resultado del juego. Los resultados demuestran que la elección de uno de estos modelos determina el resultado final.
El segundo trabajo se dedica a crear en modelo dinámico de formación de coaliciones en el que los individuos no saben el valor que tiene cada coalición para ellos. El modelo crea un proceso de Markov no estacionario. Nuestros resultados demuestran que los puntos fijos del sistema se pueden aproximar por una secuencia de dinámicas perturbadas en los que los jugadores saben el valor de las coaliciones.
En el ultimo trabajo analizamos la dinámica de un mercado usando un modelo computacional. El enfoque del trabajo es la influencia de los hábitos de los consumidores sobre la estructura del mercado. Los resultados demuestran que algunas de las características del comportamiento de los consumidores pueden sostener la diversidad en calidades y tamaño de las empresas en el mercado.
This thesis focuses on studying the way in which individuals' adaptation mechanizms influence their behavior and the outcomes in different games. In all the models presented here the emphasis is put on the adaptation process and its elements, rather than on the equilibrium behavior of the players.
The thesis consists of three papers.
The first one focuses on the importance of the way the information is exchanged in the context of Repeated Prisoner's Dilemma game. In Chapter 2 we build a simulation model imitating the structure of human reasoning in order to study how people face a Repeated Prisoner's Dilemma game. The results are ranged starting from individual learning in which case the worst result -defection- is obtained, passing through a partial imitation, where individuals could end up in cooperation or defection, and reaching the other extreme of social learning, where mutual cooperation can be obtained. The influence of some particular strategies on the attainment of cooperation is also considered. Those differences in the results of the three scenarios we have constructed suggest that one should be very careful when deciding which one to choose.
Chapter 3 studies the process of coalition formation when players are unsure about the true benefit of belonging to a given coalition. Under such strong incomplete information scenario, we use a Case-Based Decision Theory approach to study the underlying dynamic process. We show that such process can be modeled as a non-stationary Markov process. Our main result shows that any rest point of such dynamics can be approached by a sequence of similar "perturbed" dynamics in which players learn all the information about the value of each possible coalition
In Chapter 4 we study the dynamics of an experience good market using a two-sided adaptation Agent Based Computational Economics (ACE) model. The main focus of the analysis is the influence of consumers' habits on market structure. Our results show that given characteristics of consumers' behavior might sustain the diversity in the market both in terms of quality and firms' size. We observe that the more adaptive one side of the market is, the more the market reflects its interests.
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Leevers, Hilary Janet. "Children's logical reasoning." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362050.

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Brandano, Sergio. "Modelling causal reasoning." Thesis, Queen Mary, University of London, 2009. http://qmro.qmul.ac.uk/xmlui/handle/123456789/625.

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Although human causal reasoning is widely acknowledged as an object of scientific enquiry, there is little consensus on an appropriate measure of progress. Up-to-date evidence of the standard method of research in the field shows that this method has been rejected at the birth of modern science. We describe an instance of the standard scientific method for modelling causal reasoning (causal calculators). The method allows for uniform proofs of three relevant computational properties: correctness of the model with respect to the intended model, full abstraction of the model (function) with respect to the equivalence of reasoning scenarios (input), and formal relations of equivalence and subsumption between models. The method extends and exploits the systematic paradigm [Handbook of Logic in Artificial Intelligence and Logic Programming, volume IV, p. 439-498, Oxford 1995] to fit with our interpretation of it. Using the described method, we present results for some major models, with an updated summary spanning seventy-two years of research in the field.
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Книги з теми "Reasoning"

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Adler, Jonathan E., and Lance J. Rips, eds. Reasoning. Cambridge: Cambridge University Press, 2008. http://dx.doi.org/10.1017/cbo9780511814273.

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Smith, Gary. Statistical reasoning. 3rd ed. Boston: Allyn and Bacon, 1991.

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Traub, Jim. Subjective reasoning. Stamford, Conn: Champion International Corp., 1992.

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4

Blanchette, Jasmin, Laura Kovács, and Dirk Pattinson, eds. Automated Reasoning. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-10769-6.

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Galmiche, Didier, Stephan Schulz, and Roberto Sebastiani, eds. Automated Reasoning. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94205-6.

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Antoniou, Grigoris, Uwe Aßmann, Cristina Baroglio, Stefan Decker, Nicola Henze, Paula-Lavinia Patranjan, and Robert Tolksdorf, eds. Reasoning Web. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74615-7.

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Stones, Rob. Sociological Reasoning. London: Macmillan Education UK, 1996. http://dx.doi.org/10.1007/978-1-349-24737-0.

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Brown, Frank Markham. Boolean Reasoning. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4757-2078-5.

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Bonnefon, Jean-François. Reasoning Unbound. London: Palgrave Macmillan UK, 2017. http://dx.doi.org/10.1057/978-1-137-60049-3.

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Erdem, Esra, Joohyung Lee, Yuliya Lierler, and David Pearce, eds. Correct Reasoning. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30743-0.

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Частини книг з теми "Reasoning"

1

Finocchiaro, Maurice A. "Reasoning about reasoning." In Practical Reasoning, 167–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61313-7_71.

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Shaenfield, David E., and Deanna Kuhn. "Reasoning." In Encyclopedia of Adolescence, 2309–16. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-1695-2_18.

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Schrader, Aaron, and Rik Carl D'Amato. "Reasoning." In Encyclopedia of Clinical Neuropsychology, 2119. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-0-387-79948-3_1483.

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Schrader, Aaron, and Rik Carl D’Amato. "Reasoning." In Encyclopedia of Clinical Neuropsychology, 1. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56782-2_1483-2.

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Schrader, Aaron, and Rik Carl D’Amato. "Reasoning." In Encyclopedia of Clinical Neuropsychology, 2946–47. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-57111-9_1483.

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Chapman, Nick, Simon Finn, and Michael P. Fourman. "Reasoning." In Practical Formal Methods for Hardware Design, 184–216. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60641-0_10.

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Shekhar, Shashi, and Hui Xiong. "Reasoning." In Encyclopedia of GIS, 955. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_1090.

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Shaenfield, David E., and Deanna Kuhn. "Reasoning." In Encyclopedia of Adolescence, 3063–71. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-33228-4_18.

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Russow, Lilly-Marlene. "Reasoning." In Life Science Ethics, 31–66. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-8792-8_3.

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McComas, William F. "Reasoning." In The Language of Science Education, 83. Rotterdam: SensePublishers, 2014. http://dx.doi.org/10.1007/978-94-6209-497-0_73.

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Тези доповідей конференцій з теми "Reasoning"

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Bottino, Rosa Maria, Michela Ott, and M. Tavella. "Reasoning on Reasoning through Serious Games." In 2012 IEEE 12th International Conference on Advanced Learning Technologies (ICALT). IEEE, 2012. http://dx.doi.org/10.1109/icalt.2012.225.

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Miller, David P. "Temporal reasoning." In the 18th conference. New York, New York, USA: ACM Press, 1986. http://dx.doi.org/10.1145/318242.318472.

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O'Hearn, Peter W. "Continuous Reasoning." In LICS '18: 33rd Annual ACM/IEEE Symposium on Logic in Computer Science. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3209108.3209109.

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Jaya, A., and G. V. Uma. "An intelligent approach for reasoning the stories using case based reasoning and rule based reasoning." In Multi-Agent Systems (IAMA 2009). IEEE, 2009. http://dx.doi.org/10.1109/iama.2009.5228036.

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Ge, Qiang, and Fengbin Zheng. "Study on Family Relations Reasoning Based on Automated Reasoning." In 2010 International Conference on Computational Intelligence and Software Engineering (CiSE). IEEE, 2010. http://dx.doi.org/10.1109/cise.2010.5677058.

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Voronkov, Andrei. "Reasoning with Quantifiers and Theories Using Saturation-Based Reasoning." In 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC). IEEE, 2018. http://dx.doi.org/10.1109/synasc.2018.00015.

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7

Li, Po-Sheng, Alan Liu, and Pei-Chuan Zhou. "Context reasoning for smart homes using case-based reasoning." In 2014 International Symposium on Consumer Electronics (ICSE). IEEE, 2014. http://dx.doi.org/10.1109/isce.2014.6884414.

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8

Schuet, Stefan, Joshua E. Baculi, Vaishali Hosagrahara, Vahram Stepanyan, Katelyn Jarvis, and Kalmanje S. Krishnakumar. "Reasoning Service Exemplars for NASA’s Data and Reasoning Fabric." In AIAA SCITECH 2023 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2023. http://dx.doi.org/10.2514/6.2023-1658.

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9

Mirzaee, Roshanak, and Parisa Kordjamshidi. "Disentangling Extraction and Reasoning in Multi-hop Spatial Reasoning." In Findings of the Association for Computational Linguistics: EMNLP 2023. Stroudsburg, PA, USA: Association for Computational Linguistics, 2023. http://dx.doi.org/10.18653/v1/2023.findings-emnlp.221.

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10

Fekete, Alan. "Reasoning about programs." In the twenty-fourth SIGCSE technical symposium. New York, New York, USA: ACM Press, 1993. http://dx.doi.org/10.1145/169070.169410.

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Звіти організацій з теми "Reasoning"

1

Bass, Len, James Ivers, Mark Klein, and Paulo Merson. Reasoning Frameworks. Fort Belvoir, VA: Defense Technical Information Center, July 2005. http://dx.doi.org/10.21236/ada441248.

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2

Collins, Allan, Mark Burstein, and Michelle Baker. Human Plausible Reasoning. Fort Belvoir, VA: Defense Technical Information Center, July 1988. http://dx.doi.org/10.21236/ada197426.

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3

Bock, Conrad, Michael Gruninger, Don Libes, Joshua Lubell, and Eswaran Subrahmanian. Evaluating reasoning systems. Gaithersburg, MD: National Institute of Standards and Technology, 2006. http://dx.doi.org/10.6028/nist.ir.7310.

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4

Halpern, Joseph Y. Reasoning Under Uncertainty. Fort Belvoir, VA: Defense Technical Information Center, January 1995. http://dx.doi.org/10.21236/ada295372.

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5

Davis, Randall, and Walter C. Hamscher. Model-Based Reasoning: Troubleshooting. Fort Belvoir, VA: Defense Technical Information Center, July 1988. http://dx.doi.org/10.21236/ada201614.

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6

Konolige, Kurt G. Distributed Reasoning and Planning. Fort Belvoir, VA: Defense Technical Information Center, August 1993. http://dx.doi.org/10.21236/ada268682.

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7

McLean, John. Reasoning About Security Models. Fort Belvoir, VA: Defense Technical Information Center, January 1987. http://dx.doi.org/10.21236/ada465058.

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8

Bittner, Thomas. Approximate Qualitative Temporal Reasoning. Fort Belvoir, VA: Defense Technical Information Center, January 2001. http://dx.doi.org/10.21236/ada465990.

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9

Pisan, Yusuf. Visual Reasoning with Graphs. Fort Belvoir, VA: Defense Technical Information Center, January 1994. http://dx.doi.org/10.21236/ada466292.

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10

Mulgaonkar, Prasanna. Data Driven Spatial Reasoning. Fort Belvoir, VA: Defense Technical Information Center, October 1991. http://dx.doi.org/10.21236/ada242727.

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