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Readings in Nonmonotonic Reasoning

Morgan Kauffman (1980)

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  1. Deliberation, Judgement and the Nature of Evidence.Jon Williamson - unknown
    A normative Bayesian theory of deliberation and judgement requires a procedure for merging the evidence of a collection of agents. In order to provide such a procedure, one needs to ask what the evidence is that grounds Bayesian probabilities. After finding fault with several views on the nature of evidence (the views that evidence is knowledge; that evidence is whatever is fully believed; that evidence is observationally set credence; that evidence is information), it is argued that evidence is whatever is (...)
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  • Similarity and rules: distinct? exhaustive? empirically distinguishable?Ulrike Hahn & Nick Chater - 1998 - Cognition 65 (2-3):197-230.
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  • Gödel redux.Alexis Manaster-Ramer, Walter J. Savitch & Wlodek Zadrozny - 1990 - Behavioral and Brain Sciences 13 (4):675-676.
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  • The pretender's new clothes.Tim Smithers - 1990 - Behavioral and Brain Sciences 13 (4):683-684.
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  • Is mathematical insight algorithmic?Martin Davis - 1990 - Behavioral and Brain Sciences 13 (4):659-660.
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  • Computations over abstract categories of representation.Roy Eagleson - 1990 - Behavioral and Brain Sciences 13 (4):661-662.
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  • Strong AI and the problem of “second-order” algorithms.Gerd Gigerenzer - 1990 - Behavioral and Brain Sciences 13 (4):663-664.
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  • Selecting for the con in consciousness.Deborah Hodgkin & Alasdair I. Houston - 1990 - Behavioral and Brain Sciences 13 (4):668-669.
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  • A long time ago in a computing lab far, far away….Jeffery L. Johnson, R. H. Ettinger & Timothy L. Hubbard - 1990 - Behavioral and Brain Sciences 13 (4):670-670.
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  • Odd Choices: On the Rationality of Some Alleged Anomalies of Decision and Inference.Hans Rott - 2011 - Topoi 30 (1):59-69.
    This paper presents a number of apparent anomalies in rational choice scenarios, and their translation into the logic of everyday reasoning. Three classes of examples that have been discussed in the context of probabilistic choice since the 1960s (by Debreu, Tversky and others) are analyzed in a non-probabilistic setting. It is shown how they can at the same time be regarded as logical problems that concern the drawing of defeasible inferences from a given information base. I argue that initial appearances (...)
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  • Defeasible Reasoning + Partial Models: A Formal Framework for the Methodology of Research Programs. [REVIEW]Fernando Tohmé, Claudio Delrieux & Otávio Bueno - 2011 - Foundations of Science 16 (1):47-65.
    In this paper we show that any reasoning process in which conclusions can be both fallible and corrigible can be formalized in terms of two approaches: (i) syntactically, with the use of defeasible reasoning, according to which reasoning consists in the construction and assessment of arguments for and against a given claim, and (ii) semantically, with the use of partial structures, which allow for the representation of less than conclusive information. We are particularly interested in the formalization of scientific reasoning, (...)
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  • Logicism, Mental Models and Everyday Reasoning: Reply to Garnham.Nick Chater & Mike Oaksford - 1993 - Mind and Language 8 (1):72-89.
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  • Mental probability logic.Niki Pfeifer & Gernot D. Kleiter - 2009 - Behavioral and Brain Sciences 32 (1):98-99.
    We discuss O&C's probabilistic approach from a probability logical point of view. Specifically, we comment on subjective probability, the indispensability of logic, the Ramsey test, the consequence relation, human nonmonotonic reasoning, intervals, generalized quantifiers, and rational analysis.
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  • What should default reasoning be, by default?Jeff Pelletier - unknown
    This is a position paper concerning the role of empirical studies of human default reasoning in the formalization of AI theories of default reasoning. We note that AI motivates its theoretical enterprise by reference to human skill at default reasoning, but that the actual research does not make any use of this sort of information and instead relies on intuitions of individual investigators. We discuss two reasons theorists might not consider human performance relevant to formalizing default reasoning: (a) that intuitions (...)
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  • Reviewing Reduction in a Preferential Model‐Theoretic Context.Emma Ruttkamp & Johannes Heidema - 2005 - International Studies in the Philosophy of Science 19 (2):123 – 146.
    In this article, we redefine classical notions of theory reduction in such a way that model-theoretic preferential semantics becomes part of a realist depiction of this aspect of science. We offer a model-theoretic reconstruction of science in which theory succession or reduction is often better - or at a finer level of analysis - interpreted as the result of model succession or reduction. This analysis leads to 'defeasible reduction', defined as follows: The conjunction of the assumptions of a reducing theory (...)
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  • Beliefs in conditionals vs. conditional beliefs.Hannes Leitgeb - 2007 - Topoi 26 (1):115-132.
    On the basis of impossibility results on probability, belief revision, and conditionals, it is argued that conditional beliefs differ from beliefs in conditionals qua mental states. Once this is established, it will be pointed out in what sense conditional beliefs are still conditional, even though they may lack conditional contents, and why it is permissible to still regard them as beliefs, although they are not beliefs in conditionals. Along the way, the main logical, dispositional, representational, and normative properties of conditional (...)
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  • On nonmonotonic reasoning with the method of sweeping presumptions.Steven O. Kimbrough & Hua Hua - 1991 - Minds and Machines 1 (4):393-416.
    Reasoning almost always occurs in the face of incomplete information. Such reasoning is nonmonotonic in the sense that conclusions drawn may later be withdrawn when additional information is obtained. There is an active literature on the problem of modeling such nonmonotonic reasoning, yet no category of method-let alone a single method-has been broadly accepted as the right approach. This paper introduces a new method, called sweeping presumptions, for modeling nonmonotonic reasoning. The main goal of the paper is to provide an (...)
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  • Logical Disagreement.Frederik J. Andersen - 2024 - Dissertation, University of St. Andrews
    While the epistemic significance of disagreement has been a popular topic in epistemology for at least a decade, little attention has been paid to logical disagreement. This monograph is meant as a remedy. The text starts with an extensive literature review of the epistemology of (peer) disagreement and sets the stage for an epistemological study of logical disagreement. The guiding thread for the rest of the work is then three distinct readings of the ambiguous term ‘logical disagreement’. Chapters 1 and (...)
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  • A semantic approach to nonmonotonic reasoning: Inference operations and choice.Sten Lindström - 2022 - Theoria 88 (3):494-528.
    Theoria, Volume 88, Issue 3, Page 494-528, June 2022.
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  • How much of commonsense and legal reasoning is formalizable? A review of conceptual obstacles.James Franklin - 2012 - Law, Probability and Risk 11:225-245.
    Fifty years of effort in artificial intelligence (AI) and the formalization of legal reasoning have produced both successes and failures. Considerable success in organizing and displaying evidence and its interrelationships has been accompanied by failure to achieve the original ambition of AI as applied to law: fully automated legal decision-making. The obstacles to formalizing legal reasoning have proved to be the same ones that make the formalization of commonsense reasoning so difficult, and are most evident where legal reasoning has to (...)
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  • A Semantic Approach to Nonmonotonic Reasoning: Inference Operations and Choice, Uppsala Prints and Preprints in Philosophy, 1994, no 10.Sten Lindström - manuscript
    This paper presents a uniform semantic treatment of nonmonotonic inference operations that allow for inferences from infinite sets of premises. The semantics is formulated in terms of selection functions and is a generalization of the preferential semantics of Shoham (1987), (1988), Kraus, Lehman, and Magidor (1990) and Makinson (1989), (1993). A selection function picks out from a given set of possible states (worlds, situations, models) a subset consisting of those states that are, in some sense, the most preferred ones. A (...)
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  • Monotonic and Non-monotonic Embeddings of Anselm’s Proof.Jacob Archambault - 2017 - Logica Universalis 11 (1):121-138.
    A consequence relation \ is monotonic iff for premise sets \ and conclusion \, if \, \, then \; and non-monotonic if this fails in some instance. More plainly, a consequence relation is monotonic when whatever is entailed by a premise set remains entailed by any of its supersets. From the High Middle Ages through the Early Modern period, consequence in theology is assumed to be monotonic. Concomitantly, to the degree the argument formulated by Anselm at Proslogion 2–4 is taken (...)
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  • A Social Contract Account for CSR as an Extended Model of Corporate Governance : Compliance, Reputation and Reciprocity.Lorenzo Sacconi - 2007 - Journal of Business Ethics 75 (1):77-96.
    This essay seeks to give a contractarian foundation to the concept of Corporate Social Responsibility, meant as an extended model of corporate governance of the firm. Whereas, justificatory issues have been discussed in a related paper, in this essay I focus on the implementation of and compliance with this normative model. The theory of reputation games, with reference to the basic game of trust, is introduced in order to make sense of self-regulation as a way to implement the social contract (...)
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  • (1 other version)Formalizing falsification: Three delete operations.Rüdiger Schätz - 1990 - Zeitschrift fur mathematische Logik und Grundlagen der Mathematik 36 (5):455-470.
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  • Systematic, unconscious thought is the place to anchor quantum mechanics in the mind.Thomas Roeper - 1990 - Behavioral and Brain Sciences 13 (4):681-682.
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  • On “seeing” the truth of the Gödel sentence.George Boolos - 1990 - Behavioral and Brain Sciences 13 (4):655-656.
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  • Betting your life on an algorithm.Daniel C. Dennett - 1990 - Behavioral and Brain Sciences 13 (4):660-661.
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  • Time-delays in conscious processes.Benjamin Libet - 1990 - Behavioral and Brain Sciences 13 (4):672-672.
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  • A Formal Model of Legal Argumentation.Giovanni Sartor - 1994 - Ratio Juris 7 (2):177-211.
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  • Supervaluational anti-realism and logic.Stig Alstrup Rasmussen - 1990 - Synthese 84 (1):97 - 138.
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  • Penrose's Platonism.James Higginbotham - 1990 - Behavioral and Brain Sciences 13 (4):667-668.
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  • The emperor's old hat.Don Perlis - 1990 - Behavioral and Brain Sciences 13 (4):680-681.
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  • The Three Faces of Defeasibility in the Law.Henry Prakken & Giovanni Sartor - 2004 - Ratio Juris 17 (1):118-139.
    In this paper we will analyse the issue of defeasibility in the law, taking into account research carried out in philosophy, artificial intelligence and legal theory. We will adopt a very general idea of legal defeasibility, in which we will include all different ways in which certain legal conclusions may need to be abandoned, though no mistake was made in deriving them. We will argue that defeasibility in the law involves three different aspects, which we will call inference‐based defeasibility, process‐based (...)
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  • (1 other version)The philosophy of computer science.Raymond Turner - 2013 - Stanford Encyclopedia of Philosophy.
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  • On dialethism.Laura Goodship - 1996 - Australasian Journal of Philosophy 74 (1):153 – 161.
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  • Governing ignorance through abduction.Lorenzo Magnani - 2021 - Logic Journal of the IGPL 29 (4):409-424.
    I will analyse three fundamental ways of governing ignorance though abduction, which are essential from an eco-cognitive and eco-logical point of view, in which the central role in human cognition of natural and artefactual environment is taken into account. First of all, according to the so-called GW-schema, proposed by Gabbay and Woods, abduction presents an ignorance-preserving or (ignorance-mitigating) character: given the fact that the abduced hypotheses aim at becoming truths, the basic ignorance is neither solved nor left untouched. Second, I (...)
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  • Minds beyond brains and algorithms.Jan M. Zytkow - 1990 - Behavioral and Brain Sciences 13 (4):691-692.
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  • Perceptive questions about computation and cognition.Jon Doyle - 1990 - Behavioral and Brain Sciences 13 (4):661-661.
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  • Sense Generation: A “Quasi‐Classical” Approach to Concepts and Concept Combination.Bradley Franks - 1995 - Cognitive Science 19 (4):441-505.
    This article presents a detailed formal approach to concepts and concept combination. Sense generation is a competence‐level theory that attempts to respect constraints from the various cognitive sciences, and postulates “quasi‐classical” conceptual structures where attributes receive only one value (but are defeasible and so do not represent necessary and sufficient conditions on category membership) and where classification is binary (but explicitly context‐sensitive). It is also argued that any general theory of concepts must account for “privative” combinations (e.g., stone lion, fake (...)
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  • 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 as a (...)
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  • Precis of the emperor's new mind.Roger Penrose - 1990 - Behavioral and Brain Sciences 13 (4):643-705.
    The emperor's new mind (hereafter Emperor) is an attempt to put forward a scientific alternative to the viewpoint of according to which mental activity is merely the acting out of some algorithmic procedure. John Searle and other thinkers have likewise argued that mere calculation does not, of itself, evoke conscious mental attributes, such as understanding or intentionality, but they are still prepared to accept the action the brain, like that of any other physical object, could in principle be simulated by (...)
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  • Seeing truth or just seeming true?Adina Roskies - 1990 - Behavioral and Brain Sciences 13 (4):682-683.
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  • Models for belief revision.Raymundo Morado - 1992 - Philosophical Issues 2:227-247.
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  • Je nemonotónní logika logikou?Ivo Pezlar - 2012 - Pro-Fil 13 (1):41.
    Nemonotónní logika vznikla za účelem systematicky zachytit tzv. zrušitelné uvažování, tj. typ každodenního uvažování, které vede jen k provizorně platným argumentům, jenž mohou být následně staženy s příchodem nových informací. Tím se ovšem nemonotónní logika dostává do ostrého kontrastu s klasickou logikou, která je monotónní, tj. žádné dodatečné premisy nemohou zrušit jednou již platné argumenty. To bylo pro mnohé dostatečným důvodem k tomu, aby nemonotónní logice upřeli status logiky. V tomto textu si ukážeme, že takový závěr je příliš unáhlený a (...)
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  • And then a miracle happens….Keith E. Stanovich - 1990 - Behavioral and Brain Sciences 13 (4):684-685.
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  • Exactly which emperor is Penrose talking about?John K. Tsotsos - 1990 - Behavioral and Brain Sciences 13 (4):686-687.
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  • Computability, consciousness, and algorithms.Robert Wilensky - 1990 - Behavioral and Brain Sciences 13 (4):690-691.
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  • The frame problem and the treatment of prediction.Mark Sprevak - 2005 - In Lorenzo Magnani & Riccardo Dossena (eds.), Computing, Philosophy and Cognition: Proceedings of the European Computing and Philosophy Conference (ECAP 2004). College Publications. pp. 4--349.
    The frame problem is a problem in artificial intelligence that a number of philosophers have claimed has philosophical relevance. The structure of this paper is as follows: (1) An account of the frame problem is given; (2) The frame problem is distinguished from related problems; (3) The main strategies for dealing with the frame problem are outlined; (4) A difference between commonsense reasoning and prediction using a scientific theory is argued for; (5) Some implications for the..
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  • Theory structure, reduction, and disciplinary integration in biology.Kenneth F. Schaffner - 1993 - Biology and Philosophy 8 (3):319-347.
    This paper examines the nature of theory structure in biology and considers the implications of those theoretical structures for theory reduction. An account of biological theories as interlevel prototypes embodying causal sequences, and related to each other by strong analogies, is presented, and examples from the neurosciences are provided to illustrate these middle-range theories. I then go on to discuss several modifications of Nagel''s classical model of theory reduction, and indicate at what stages in the development of reductions these models (...)
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  • Between Turing and quantum mechanics there is body to be found.Francisco J. Varela - 1990 - Behavioral and Brain Sciences 13 (4):687-688.
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