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  1. A logic for default reasoning.Ray Reiter - 1980 - Artificial Intelligence 13 (1-2):81-137.
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  • A truth maintenance system.Jon Doyle - 1979 - Artificial Intelligence 12 (3):231-272.
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  • Non-monotonic logic I.Drew McDermott & Jon Doyle - 1980 - Artificial Intelligence 13 (1-2):41-72.
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  • Nonmonotonic logic and temporal projection.Steve Hanks & Drew McDermott - 1987 - Artificial Intelligence 33 (3):379-412.
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  • Model-preference default theories.Bart Selman & Henry A. Kautz - 1990 - Artificial Intelligence 45 (3):287-322.
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  • Nonmonotonicity and the scope of reasoning.David W. Etherington, Sarit Kraus & Donald Perlis - 1991 - Artificial Intelligence 52 (3):221-261.
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  • Model-Theoretic Logics.Jon Barwise & Solomon Feferman - 2017 - Cambridge University Press.
    This book brings together several directions of work in model theory between the late 1950s and early 1980s.
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  • Deduction.Philip Nicholas Johnson-Laird & Ruth M. J. Byrne - 1991 - Psychology Press.
    In this study on deduction, the authors argue that people reason by imagining the relevant state of affairs, ie building an internal model of it, formulating a tentative conclusion based on this model and then searching for alternative models.
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  • Syllogistic inference.P. N. Johnson-Laird & Bruno G. Bara - 1984 - Cognition 16 (1):1-61.
    This paper reviews current psychological theories of syllogistic inference and establishes that despite their various merits they all contain deficiencies as theories of performance. It presents the results of two experiments, one using syllogisms and the other using three-term series problems, designed to elucidate how the arrangement of terms within the premises affects performance. These data are used in the construction of a theory based on the hypothesis that reasoners construct mental models of the premises, formulate informative conclusions about the (...)
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  • Response to Hanks and McDermott: Temporal Evolution of Beliefs and Beliefs about Temporal Evolution.Ronald P. Loui - 1987 - Cognitive Science 11 (3):283-297.
    This paper critically evaluates the celebrated paper of Hanks and McDermott on temporal projection, non-monotonic reasoning, and the frame problem. First I argue against their intuitions, and a fortiori, against their proposed solution. Next, I suggest how the solution they desire could be obtained, were they willing to represent the problem a bit differently.
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  • Circumscription — A Form of Non-Monotonic Reasoning.John McCarthy - 1980 - Artificial Intelligence 13 (1-2):27–39.
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  • Against Logicist Cognitive Science.Mike Oaksford & Nick Chater - 1991 - Mind and Language 6 (1):1-38.
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  • Semantic Considerations on nonmonotonic Logic.Robert C. Moore - 1985 - Artificial Intelligence 25 (1):75-94.
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  • Understanding Computers and Cognition: A New Foundation for Design.Terry Winograd & Fernando Flores - 1987 - Addison-Wesley.
    Understanding Computers and Cognition presents an important and controversial new approach to understanding what computers do and how their functioning is related to human language, thought, and action. While it is a book about computers, Understanding Computers and Cognition goes beyond the specific issues of what computers can or can't do. It is a broad-ranging discussion exploring the background of understanding in which the discourse about computers and technology takes place. Understanding Computers and Cognition is written for a wide audience, (...)
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  • On language and connectionism: Analysis of a parallel distributed processing model of language acquisition.Steven Pinker & Alan Prince - 1988 - Cognition 28 (1-2):73-193.
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  • Autonomy, implementation and cognitive architecture: A reply to Fodor and Pylyshyn.Nick Chater & Mike Oaksford - 1990 - Cognition 34 (1):93-107.
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  • Connectionism and cognitive architecture: A critical analysis.Jerry A. Fodor & Zenon W. Pylyshyn - 1988 - Cognition 28 (1-2):3-71.
    This paper explores the difference between Connectionist proposals for cognitive a r c h i t e c t u r e a n d t h e s o r t s o f m o d e l s t hat have traditionally been assum e d i n c o g n i t i v e s c i e n c e . W e c l a i m t h a t t h (...)
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  • (1 other version)Minds, brains, and programs.John Searle - 1980 - Behavioral and Brain Sciences 3 (3):417-57.
    What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...)
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  • A rational reconstruction of nonmonotonic truth maintenance systems.Charles Elkan - 1990 - Artificial Intelligence 43 (2):219-234.
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  • Conditional entailment: Bridging two approaches to default reasoning.Hector Geffner & Judea Pearl - 1992 - Artificial Intelligence 53 (2-3):209-244.
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  • Believability and syllogistic reasoning.Jane Oakhill, P. N. Johnson-Laird & Alan Garnham - 1989 - Cognition 31 (2):117-140.
    In this paper we investigate the locus of believability effects in syllogistic reasoning. We identify three points in the reasoning process at which such effects could occur: the initial interpretation of premises, the examination of alternative representations of them (in all of which any valid conclusion must be true), and the “filtering” of putative conclusions. The effect of beliefs at the first of these loci is well established. In this paper we report three experiments that examine whether beliefs have an (...)
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  • The anomalous extension problem in default reasoning.Paul H. Morris - 1988 - Artificial Intelligence 35 (3):383-399.
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