Results for 'computer reasoning'

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  1.  46
    Program Verification, Defeasible Reasoning, and Two Views of Computer Science.Timothy R. Colburn - 1991 - Minds and Machines 1 (1):97-116.
    In this paper I attempt to cast the current program verification debate within a more general perspective on the methodologies and goals of computer science. I show, first, how any method involved in demonstrating the correctness of a physically executing computer program, whether by testing or formal verification, involves reasoning that is defeasible in nature. Then, through a delineation of the senses in which programs can be run as tests, I show that the activities of testing and (...)
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  2.  13
    Scaffolding Computer-Mediated Discussion to Enhance Moral Reasoning and Argumentation Quality in Pre-Service Teachers.Hüseyin Özçinar - 2015 - Journal of Moral Education 44 (2):232-251.
    This study investigated the effect of scaffolding computer-mediated discussions to improve moral reasoning and argumentation quality in pre-service teachers. Participants of this study were 76 teaching education students at a Turkish university. They were divided into three groups: a computer-supported argumentation group; a computer-mediated discussion group; and a control group. Participants in the computer-supported argumentation group were instructed in argumentation, and were provided with note starters and graphical argumentation tools. The computer-mediated discussion group, however, (...)
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  3.  16
    A Logical Argumentation Model for Computer-Assisted Reasoning.Mario Borillo - 1990 - Argumentation 4 (4):397-414.
    The study of some real reasonings (observed in the Humanities) reveals the very heterogeneous nature of the arguments used in the building of scientific knowledge and the complexity of their overall architecture. The building of a formal theory of the trace of these mental processes on the classical grounds of logic seems quite impossible. Instead, we propose a flexible methodology based on some local formal models, integrated in a global strategy. This strategy allows an empirical, but systematic, description of the (...)
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  4. Clausal Form Logic an Introduction to the Logic of Computer Reasoning.Tom Richards - 1989
  5.  27
    Reasoning About Partial Functions with the Aid of a Computer.William M. Farmer - 1995 - Erkenntnis 43 (3):279 - 294.
    Partial functions are ubiquitous in both mathematics and computer science. Therefore, it is imperative that the underlying logical formalism for a general-purpose mechanized mathematics system provide strong support for reasoning about partial functions. Unfortunately, the common logical formalisms — first-order logic, type theory, and set theory — are usually only adequate for reasoning about partial functionsin theory. However, the approach to partial functions traditionally employed by mathematicians is quite adequatein practice. This paper shows how the traditional approach (...)
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  6. Medical Diagnostic Reasoning: Epistemological Modeling as a Strategy for Design of Computer-Based Consultation Programs.Giovanni Barosi, Lorenzo Magnani & Mario Stefanelli - 1993 - Theoretical Medicine and Bioethics 14 (1).
    The complexity of cognitive emulation of human diagnostic reasoning is the major challenge in the implementation of computer-based programs for diagnostic advice in medicine. We here present an epistemological model of diagnosis with the ultimate goal of defining a high-level language for cognitive and computational primitives. The diagnostic task proceeds through three different phases: hypotheses generation, hypotheses testing and hypotheses closure. Hypotheses generation has the inferential form of abduction (from findings to hypotheses) constrained under the criterion of plausibility. (...)
     
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  7.  12
    Criteria for Evaluating a Computer Aid to Clinical Reasoning.C. Whitbeck & R. Brooks - 1983 - Journal of Medicine and Philosophy 8 (1):51-66.
    The acceptance or rejection of computer aids to clinical reasoning is determined not only by the preferences and prejudices of potential users, but also by whether the output generated by the computer aid represents sound clinical judgment. This paper deals with the issue of the appropriate criteria for evaluating the clinical ‘reasoning’ of computer aids. Evaluation of a computer aid should include an assessment of the accuracy or appropriateness of its conclusions and an assessment (...)
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  8. Using Computer-Assisted Argument Mapping to Teach Reasoning to Students.Martin Davies, Ashley Barnett & Tim van Gelder - 2019 - In J. Anthony Blair (ed.), Studies in Critical Thinking. Windsor, ON, Canada: Windsor Studies in Argumentation. pp. 131-176.
    Argument mapping is a way of diagramming the logical structure of an argument to explicitly and concisely represent reasoning. The use of argument mapping in critical thinking instruction has increased dramatically in recent decades. This paper overviews the innovation and provides a procedural approach for new teaches wanting to use argument mapping in the classroom. A brief history of argument mapping is provided at the end of this paper.
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  9.  39
    Moral Reasoning in Computer-Based Task Environments: Exploring the Interplay Between Cognitive and Technological Factors on Individuals' Propensity to Break Rules. [REVIEW]Jeffrey A. Roberts & David M. Wasieleski - 2012 - Journal of Business Ethics 110 (3):355-376.
    This study examines the relationship between cognitive moral development (CMD), productivity features of information technology (IT) and unethical behavior or misconduct. Using an experimental design that randomly assigns subjects to one of four unique technology conditions, we assess the relationship between a subjects' predominant level of CMD and ethical misconduct on IT-oriented work tasks. Our results show that both higher levels of CMD and increased levels of IT productivity features at one's disposal have a significant role to play in explaining (...)
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  10.  27
    Zohar Manna and Richard Waldinger. The Logical Basis for Computer Programming. Volume I. Deductive Reasoning. Addison-Wesley Series in Computer Science. Addison-Wesley Publishing Company, Reading, Mass., Etc., 1985, Xii + 618 Pp. - Zohar Manna and Richard Waldinger. The Logical Basis for Computer Programming. Volume II. Deductive Systems. Addison-Wesley Series in Computer Science. Addison-Wesley Publishing Company, Reading, Mass., Etc., 1990, Xiii + 642 Pp. [REVIEW]Hans Klene Buning - 1995 - Journal of Symbolic Logic 60 (4):1326-1327.
  11.  12
    Temporal Logics and Their Applications, Edited by Antony Galton, Academic Press, London, San Diego, Etc., 1987, Xii + 244 Pp.—Therein: - Antony Galton. Temporal Logic and Computer Science: An Overview. Pp. 1– 52. - Howard Barringer. The Use of Temporal Logic in the Compositional Specification of Concurrent Systems. Pp. 53– 90. - Roger Hale. Temporal Logic Programming. Pp. 91– 119. - Fariba Sadri. Three Recent Approaches to Temporal Reasoning. Pp. 121– 168. - Antony Galton. The Logic of Occurrence. Pp. 169– 196. - Dov Gabbay. Modal and Temporal Logic Programming. Pp. 197– 237. [REVIEW]Luis Fariñas Del Cerro - 1990 - Journal of Symbolic Logic 55 (1):364-366.
  12.  11
    Alan Bundy. The Computer Modelling of Mathematical Reasoning. Academic Press, London Etc. 1983, Xiv + 322 Pp. [REVIEW]Vladimir Lifschitz - 1987 - Journal of Symbolic Logic 52 (2):555-557.
  13.  2
    A Jaśkowski-Style System of Computer-Assisted Reasoning.Witold Marciszewski - 1994 - In Jan Wolenski (ed.), Philosophical Logic in Poland. Kluwer Academic Publishers. pp. 85--101.
  14.  23
    Integrating Computer Algebra and Reasoning Through the Type System of Aldor.Erik Poll & Simon Thompson - 2000 - In Dov M. Gabbay & Maarten de Rijke (eds.), Frontiers of Combining Systems. Research Studies Press. pp. 136--150.
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  15.  3
    A Model of Common-Sense Reasoning Underlying Intentional Nonaction in Stressful Interpersonal Situations and Its Application in the Technology of Computer-Based Psychotherapy.Kenneth Mark Colby, Roger L. Gould, Gerald Aronson & Peter M. Colby - 1991 - Journal of Intelligent Systems 1 (3):259-272.
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  16.  14
    Brewka Gerhard. Nonmonotonic Reasoning: Logical Foundations of Commonsense. Cambridge Tracts in Theoretical Computer Science, No. 12. Cambridge University Press, Cambridge Etc. 1991, Xiii + 168 Pp. [REVIEW]Heinrich Herre - 1993 - Journal of Symbolic Logic 58 (3):1079-1080.
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  17.  16
    Handbook of Logic in Artificial Intelligence and Logic Programming, Volume 3, Nonmonotonic Reasoning and Uncertain Reasoning, Edited by Dov M. Gabbay, C. J. Hogger, and J. A. Robinson, with D. Nute, Handbooks of Logic in Computer Science and Artificial Intelligence and Logic Programming, Clarendon Press, Oxford University Press, Oxford, New York, Etc., 1994, Xix + 529 Pp.–. [REVIEW]G. Aldo Antonelli - 2000 - Bulletin of Symbolic Logic 6 (4):480-484.
  18.  16
    How to Run Algorithmic Information Theory on a Computer:Studying the Limits of Mathematical Reasoning.Gregory J. Chaitin - 1996 - Complexity 2 (1):15-21.
  19.  13
    Bundy Alan, Basin David, Hutter Dieter and Ireland Andrew. Rippling: Meta-Level Guidance for Mathematical Reasoning. Cambridge Tracts in Theoretical Computer Science, Vol. 56. Cambridge University Press, 2005, Xiv+ 202 Pp. [REVIEW]Joe Hurd - 2006 - Bulletin of Symbolic Logic 12 (3):498-499.
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  20.  31
    Logic in Computer Science: Modelling and Reasoning About Systems. [REVIEW]Valentin Goranko - 2006 - Journal of Logic, Language and Information 16 (1):117-120.
  21.  7
    deBessonet Cary G.. A Many-Valued Approach to Deduction and Reasoning for Artificial Intelligence. The Kluwer International Series in Engineering and Computer Science. Kluwer Academic Publishers, Boston, Dordrecht, and London, 1991, Xviii+ 248 Pp. [REVIEW]Robert Stärk - 1995 - Journal of Symbolic Logic 60 (4):1328-1329.
  22.  5
    Systems of Computer-Aided Reasoning for Mathematics and Natural Language.Witold Marciszewski - 1987 - In Jan T. J. Srzednicki (ed.), Initiatives in Logic. M. Nijhoff. pp. 207--223.
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  23.  3
    Review: Alan Bundy, The Computer Modelling of Mathematical Reasoning[REVIEW]Vladimir Lifschitz - 1987 - Journal of Symbolic Logic 52 (2):555-557.
  24.  3
    Narrative Vs. Logical Reasoning in Computer Ethics.John M. Artz - 1998 - Acm Sigcas Computers and Society 28 (4):3-5.
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  25. Reasoning About Update Logic', Report CS-R9312, Centre for Mathematics and Computer Science, Amsterdam.J. van Eijck & F. J. de Vries - forthcoming - Journal of Philosophical Logic.
  26. Computer Models On Mind: Computational Approaches In Theoretical Psychology.Margaret A. Boden - 1988 - Cambridge University Press.
    What is the mind? How does it work? How does it influence behavior? Some psychologists hope to answer such questions in terms of concepts drawn from computer science and artificial intelligence. They test their theories by modeling mental processes in computers. This book shows how computer models are used to study many psychological phenomena--including vision, language, reasoning, and learning. It also shows that computer modeling involves differing theoretical approaches. Computational psychologists disagree about some basic questions. For (...)
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  27.  9
    Model-Based Abductive Reasoning in Automated Software Testing.N. Angius - 2013 - Logic Journal of the IGPL 21 (6):931-942.
    Automated Software Testing (AST) using Model Checking is in this article epistemologically analysed in order to argue in favour of a model-based reasoning paradigm in computer science. Preliminarily, it is shown how both deductive and inductive reasoning are insufficient to determine whether a given piece of software is correct with respect to specified behavioural properties. Models algorithmically checked in Model Checking to select executions to be observed in Software Testing are acknowledged as analogical models which establish isomorphic (...)
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  28. How Can Computer Simulations Produce New Knowledge?Claus Beisbart - 2012 - European Journal for Philosophy of Science 2 (3):395-434.
    It is often claimed that scientists can obtain new knowledge about nature by running computer simulations. How is this possible? I answer this question by arguing that computer simulations are arguments. This view parallels Norton’s argument view about thought experiments. I show that computer simulations can be reconstructed as arguments that fully capture the epistemic power of the simulations. Assuming the extended mind hypothesis, I furthermore argue that running the computer simulation is to execute the reconstructing (...)
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  29.  12
    Computer-Supported Resolution of Measurement Conflicts: A Case-Study in Materials Science. [REVIEW]Hidde de Jong, Nicolaas Mars & Paul van der Vet - 1999 - Foundations of Science 4 (4):427-461.
    Resolving conflicts between different measurements ofa property of a physical system may be a key step in a discoveryprocess. With the emergence of large-scale databases and knowledgebases with property measurements, computer support for the task ofconflict resolution has become highly desirable. We will describe amethod for model-based conflict resolution and the accompanyingcomputer tool KIMA, which have been applied in a case-study inmaterials science. In order to be a useful aid to scientists, the toolneeds to be integrated with other tools (...)
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  30. Heuristic Methods for Computer Ethics.Walter Maner - 2002 - In James Moor & Terrell Ward Bynum (eds.), Cyberphilosophy: The Intersection of Philosophy and Computing. Blackwell. pp. 339-365.
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  31.  15
    Casuistry and Computer Ethics.Kari Gwen Coleman - 2007 - Metaphilosophy 38 (4):471-488.
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  32.  62
    Validation of Computer Simulations From a Kuhnian Perspective.Eckhart Arnold - 2019 - In Claus Beisbart & Nicole J. Saam (eds.), Computer Simulation Validation - Fundamental Concepts, Methodological Frameworks, and Philosophical Perspectives. Heidelberg, Deutschland: Springer. pp. 203-224.
    While Thomas Kuhn's theory of scientific revolutions does not specifically deal with validation, the validation of simulations can be related in various ways to Kuhn's theory: 1) Computer simulations are sometimes depicted as located between experiments and theoretical reasoning, thus potentially blurring the line between theory and empirical research. Does this require a new kind of research logic that is different from the classical paradigm which clearly distinguishes between theory and empirical observation? I argue that this is not (...)
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  33.  47
    Scientific Theories of Computational Systems in Model Checking.Nicola Angius & Guglielmo Tamburrini - 2011 - Minds and Machines 21 (2):323-336.
    Model checking, a prominent formal method used to predict and explain the behaviour of software and hardware systems, is examined on the basis of reflective work in the philosophy of science concerning the ontology of scientific theories and model-based reasoning. The empirical theories of computational systems that model checking techniques enable one to build are identified, in the light of the semantic conception of scientific theories, with families of models that are interconnected by simulation relations. And the mappings between (...)
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  34.  10
    Reasoning About Relations.Geoffrey P. Goodwin & Philip Johnson-Laird - 2005 - Psychological Review 112 (2):468-493.
    Inferences about spatial, temporal, and other relations are ubiquitous. This article presents a novel model-based theory of such reasoning. The theory depends on 5 principles. The structure of mental models is iconic as far as possible. The logical consequences of relations emerge from models constructed from the meanings of the relations and from knowledge. Individuals tend to construct only a single, typical model. They spontaneously develop their own strategies for relational reasoning. Regardless of strategy, the difficulty of an (...)
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  35. Three Paradigms of Computer Science.Amnon H. Eden - 2007 - Minds and Machines 17 (2):135-167.
    We examine the philosophical disputes among computer scientists concerning methodological, ontological, and epistemological questions: Is computer science a branch of mathematics, an engineering discipline, or a natural science? Should knowledge about the behaviour of programs proceed deductively or empirically? Are computer programs on a par with mathematical objects, with mere data, or with mental processes? We conclude that distinct positions taken in regard to these questions emanate from distinct sets of received beliefs or paradigms within the discipline: (...)
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  36.  52
    Nonmonotonic Reasoning: Logical Foundations of Commonsense.Gerhard Brewka (ed.) - 1991 - Cambridge University Press.
    In this book the author gives a broad overview of different areas of research in nonmonotonic reasoning, and presents some new results and ideas based on his research. The guiding principles are: clarification of the different research activities in the area, which have sometimes been undertaken independently of each other; and appreciation of the fact that these research activities often represent different means to the same ends, namely sound theoretical foundations and efficient computation. The book begins with a discussion (...)
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  37.  44
    Causal Bayes Nets as Psychological Theories of Causal Reasoning: Evidence From Psychological Research.York Hagmayer - 2016 - Synthese 193 (4):1107-1126.
    Causal Bayes nets have been developed in philosophy, statistics, and computer sciences to provide a formalism to represent causal structures, to induce causal structure from data and to derive predictions. Causal Bayes nets have been used as psychological theories in at least two ways. They were used as rational, computational models of causal reasoning and they were used as formal models of mental causal models. A crucial assumption made by them is the Markov condition, which informally states that (...)
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  38. From Data to Phenomena and Back Again: Computer-Simulated Signatures.Eran Tal - 2011 - Synthese 182 (1):117-129.
    This paper draws attention to an increasingly common method of using computer simulations to establish evidential standards in physics. By simulating an actual detection procedure on a computer, physicists produce patterns of data (‘signatures’) that are expected to be observed if a sought-after phenomenon is present. Claims to detect the phenomenon are evaluated by comparing such simulated signatures with actual data. Here I provide a justification for this practice by showing how computer simulations establish the reliability of (...)
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  39.  29
    Stimulating Reflection and Self-Correcting Reasoning Through Argument Mapping: Three Approaches.Michael Hoffmann - 2018 - Topoi 37 (1):185-199.
    A large body of research in cognitive science differentiates human reasoning into two types: fast, intuitive, and emotional “System 1” thinking, and slower, more reflective “System 2” reasoning. According to this research, human reasoning is by default fast and intuitive, but that means that it is prone to error and biases that cloud our judgments and decision making. To improve the quality of reasoning, critical thinking education should develop strategies to slow it down and to become (...)
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  40.  67
    A Model of Argumentation and its Application to Legal Reasoning.Kathleen Freeman & Arthur M. Farley - 1996 - Artificial Intelligence and Law 4 (3-4):163-197.
    We present a computational model of dialectical argumentation that could serve as a basis for legal reasoning. The legal domain is an instance of a domain in which knowledge is incomplete, uncertain, and inconsistent. Argumentation is well suited for reasoning in such weak theory domains. We model argument both as information structure, i.e., argument units connecting claims with supporting data, and as dialectical process, i.e., an alternating series of moves by opposing sides. Our model includes burden of proof (...)
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  41. Verifying Time, Memory and Communication Bounds in Systems of Reasoning Agents.Natasha Alechina, Brian Logan, Hoang Nga Nguyen & Abdur Rakib - 2009 - Synthese 169 (2):385-403.
    We present a framework for verifying systems composed of heterogeneous reasoning agents, in which each agent may have differing knowledge and inferential capabilities, and where the resources each agent is prepared to commit to a goal (time, memory and communication bandwidth) are bounded. The framework allows us to investigate, for example, whether a goal can be achieved if a particular agent, perhaps possessing key information or inferential capabilities, is unable (or unwilling) to contribute more than a given portion of (...)
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  42.  38
    Neural-Symbolic Cognitive Reasoning.Artur D'Avila Garcez, Luis Lamb & Dov Gabbay - 2009 - New York: Springer.
    Humans are often extraordinary at performing practical reasoning. There are cases where the human computer, slow as it is, is faster than any artificial intelligence system. Are we faster because of the way we perceive knowledge as opposed to the way we represent it? -/- The authors address this question by presenting neural network models that integrate the two most fundamental phenomena of cognition: our ability to learn from experience, and our ability to reason from what has been (...)
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  43.  85
    Reasoning Processes in Propositional Logic.Claes Strannegård, Simon Ulfsbäcker, David Hedqvist & Tommy Gärling - 2010 - Journal of Logic, Language and Information 19 (3):283-314.
    We conducted a computer-based psychological experiment in which a random mix of 40 tautologies and 40 non-tautologies were presented to the participants, who were asked to determine which ones of the formulas were tautologies. The participants were eight university students in computer science who had received tuition in propositional logic. The formulas appeared one by one, a time-limit of 45 s applied to each formula and no aids were allowed. For each formula we recorded the proportion of the (...)
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  44.  30
    Common Sense, Reasoning, & Rationality.Renee Elio (ed.) - 2002 - Oxford University Press.
    As the eleventh volume in the New Directions in Cognitive Science series (formerly the Vancouver Studies in Cognitive Science series), this work promises superb scholarship and interdisciplinary appeal. It addresses three areas of current and varied interest: common sense, reasoning, and rationality. While common sense and rationality often have been viewed as two distinct features in a unified cognitive map, this volume offers novel, even paradoxical, views of the relationship. Comprised of outstanding essays from distinguished philosophers, it considers what (...)
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  45.  31
    Reasoning Biases, Non‐Monotonic Logics and Belief Revision.Catarina Dutilh Novaes & Herman Veluwenkamp - 2017 - Theoria 83 (1):29-52.
    A range of formal models of human reasoning have been proposed in a number of fields such as philosophy, logic, artificial intelligence, computer science, psychology, cognitive science, etc.: various logics, probabilistic systems, belief revision systems, neural networks, among others. Now, it seems reasonable to require that formal models of human reasoning be empirically adequate if they are to be viewed as models of the phenomena in question. How are formal models of human reasoning typically put to (...)
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  46.  31
    Computational Dialogic Defeasible Reasoning.Robert L. Causey - 2003 - Argumentation 17 (4):421-450.
    This article begins with an introduction to defeasible (nonmonotonic) reasoning and a brief description of a computer program, EVID, which can perform such reasoning. I then explain, and illustrate with examples, how this program can be applied in computational representations of ordinary dialogic argumentation. The program represents the beliefs and doubts of the dialoguers, and uses these propositional attitudes, which can include commonsense defeasible inference rules, to infer various changing conclusions as a dialogue progresses. It is proposed (...)
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  47.  15
    Business Ethics and Computer Ethics: The View From Poland. [REVIEW]Prof Jacek Sojka - 1996 - Science and Engineering Ethics 2 (2):191-200.
    An Aristotelian approach to understanding and teaching business ethics is presented and defended. The newly emerging field of computer ethics is also defined in an Aristotelian fashion, and an argument is made that this new field should be called “information ethics”. It is argued that values have their roots in the life and practices of a community; therefore, morality cannot be taught by training for a special way of reasoning. Transmission of values and norms occurs through socialization — (...)
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  48.  33
    Human-Oriented and Machine-Oriented Reasoning: Remarks on Some Problems in the History of Automated Theorem Proving. [REVIEW]Furio Di Paola - 1988 - AI and Society 2 (2):121-131.
    Examples in the history of Automated Theorem Proving are given, in order to show that even a seemingly ‘mechanical’ activity, such as deductive inference drawing, involves special cultural features and tacit knowledge. Mechanisation of reasoning is thus regarded as a complex undertaking in ‘cultural pruning’ of human-oriented reasoning. Sociological counterparts of this passage from human- to machine-oriented reasoning are discussed, by focusing on problems of man-machine interaction in the area of computer-assisted proof processing.
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  49.  15
    Reasoning Biases, Non‐Monotonic Logics and Belief Revision.Catarina Dutilh Novaes & Herman Veluwenkamp - 2016 - Theoria 82 (4).
    A range of formal models of human reasoning have been proposed in a number of fields such as philosophy, logic, artificial intelligence, computer science, psychology, cognitive science, etc.: various logics, probabilistic systems, belief revision systems, neural networks, among others. Now, it seems reasonable to require that formal models of human reasoning be empirically adequate if they are to be viewed as models of the phenomena in question. How are formal models of human reasoning typically put to (...)
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  50.  6
    Logical Studies of Paraconsistent Reasoning in Science and Mathematics.Peter Verdée & Holger Andreas (eds.) - 2016 - Springer Verlag.
    In this book we present a collection of papers on the topic of applying paraconsistent logic to solve inconsistency related problems in science, mathematics and computer science. The goal is to develop, compare, and evaluate different ways of applying paraconsistent logic. After more than 60 years of mainly theoretical developments in many independent systems of paraconsistent logic, we believe the time has come to compare and apply the developed systems in order to increase our philosophical understanding of reasoning (...)
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