Search results for 'Commonsense reasoning' (try it on Scholar)

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  1.  35
    Gerhard Brewka (ed.) (1991). Nonmonotonic Reasoning: Logical Foundations of Commonsense. 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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  2.  17
    Robert L. Causey (2003). Computational Dialogic Defeasible Reasoning. 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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  3.  1
    Heinrich Herre (1993). Review: Gerhard Brewka, Nonmonotonic Reasoning: Logical Foundations of Commonsense. [REVIEW] Journal of Symbolic Logic 58 (3):1079-1080.
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  4.  28
    Isaac Levi (1996). For the Sake of the Argument: Ramsey Test Conditionals, Inductive Inference, and Nonmonotonic Reasoning. Cambridge University Press.
    This book by one of the world's foremost philosophers in the fields of epistemology and logic offers an account of suppositional reasoning relevant to practical deliberation, explanation, prediction and hypothesis testing. Suppositions made 'for the sake of argument' sometimes conflict with our beliefs, and when they do, some beliefs are rejected and others retained. Thanks to such belief contravention, adding content to a supposition can undermine conclusions reached without it. Subversion can also arise because suppositional reasoning is ampliative. (...)
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  5.  19
    Rinke Hoekstra & Joost Breuker (2007). Commonsense Causal Explanation in a Legal Domain. Artificial Intelligence and Law 15 (3):281-299.
    In this paper, we present an approach to commonsense causal explanation of stories that can be used for automatically determining the liable party in legal case descriptions. The approach is based on, a core ontology for law that takes a commonsense perspective. Aside from our thesis that in the legal domain many terms still have a strong commonsense flavour, the descriptions of events in legal cases, as e.g. presented at judicial trials, are cast in commonsense terms (...)
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  6.  13
    Corina Strößner (2015). Normality and Majority: Towards a Statistical Understanding of Normality Statements. Erkenntnis 80 (4):793-809.
    Normality judgements are frequently used in everyday communication as well as in biological and social science. Moreover they became increasingly relevant to formal logic as part of defeasible reasoning. This paper distinguishes different kinds of normality statements. It is argued that normality laws like “Birds can normally fly” should be understood essentially in a statistical way. The argument has basically two parts: firstly, a statistical semantic core is mandatory for a descriptive reading of normality in order to explain the (...)
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  7.  12
    Vladimir Lifschitz (2015). The Dramatic True Story of the Frame Default. Journal of Philosophical Logic 44 (2):163-176.
    This is an expository article about the solution to the frame problem proposed in 1980 by Raymond Reiter. For years, his “frame default” remained untested and suspect. But developments in some seemingly unrelated areas of computer science—logic programming and satisfiability solvers—eventually exonerated the frame default and turned it into a basis for important applications.
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  8.  22
    Leora Morgenstern (2001). Mid-Sized Axiomatizations of Commonsense Problems: A Case Study in Egg Cracking. Studia Logica 67 (3):333-384.
    We present an axiomatization of a problem in commonsense reasoning, characterizing the proper procedure for cracking an egg and transferring its contents to a bowl. The axiomatization is mid-sized, larger than toy problems such as the Yale Shooting Problem or the Suitcase Problem, but much smaller than the comprehensive axiomatizations associated with CYC and HPKB. This size of axiomatization permits the development of non-trivial, reusable core theories of commonsense reasoning, acts as a testbed for existing theories (...)
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  9.  26
    Varol Akman, Issues in Commonsense Set Theory.
    The success of set theory as a foundation for mathematics inspires its use in arti cial intelligence, particularly in commonsense reasoning. In this survey, we brie y review classical set theory from an AI perspective, and then consider alternative set theories. Desirable properties of a possible commonsense set theory are investigated, treating di erent aspects like cumulative hierarchy, self-reference, cardinality, etc. Assorted examples from the ground-breaking research on the subject are also given.
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  10.  12
    Mujdat Pakkan & Varol Akman (1995). Issues in Commonsense Set Theory. Philosophical Explorations.
    The success of set theory as a foundation for mathematics inspires its use in artificial intelligence, particularly in commonsense reasoning. In this survey, we briefly review classical set theory from an AI perspective, and then consider alternative set theories. Desirable properties of a possible commonsense set theory are investigated, treating different aspects like cumulative hierarchy, self-reference, cardinality, etc. Assorted examples from the ground-breaking research on the subject are also given.
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  11.  10
    Mujdat Pakkan & Varol Akman (1995). Hypersolver: A Graphical Tool for Commonsense Set Theory. Philosophical Explorations.
    This paper investigates an alternative set theory (due to Peter Aczel) called Hyperset Theory. Aczel uses a graphical representation for sets and thereby allows the representation of non-well-founded sets. A program, called HYPERSOLVER, which can solve systems of equations defined in terms of sets in the universe of this new theory is presented. This may be a useful tool for commonsense reasoning.
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  12. Lynne Rudder Baker (1999). What is This Thing Called 'Commonsense Psychology'? Philosophical Explorations 2 (1):3-19.
    What is this thing called ‘Commonsense Psychology’? The first matter to settle is what the issue is here. By ‘commonsense psychology,’ I mean primarily the systems of describing, explaining and predicting human thought and action in terms of beliefs, desires, hopes, fears, expectations, intentions and other so-called propositional attitudes. Although commonsense psychology encompasses more than propositional attitudes--e.g., emotions, traits and abilities are also within its purview--belief-desire reasoning forms the core of commonsense psychology. Commonsense psychology (...)
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  13. Jim Hopkins (1996). Psychoanalytic and Scientific Reasoning. British Journal of Psychotherapy 13 (1).
    Psychoanalytic reasoning is an instance of inference to the best explanation and provides an extension of commonsense psychology that is potentially cogent, cumulative, and radical.
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  14.  22
    Nenad Mišćević (1994). Naturalism and Modal Reasoning. Grazer Philosophische Studien 49:149-173.
    A naturalistic theory of modal intuitions and modal reasoning inspired by Hintikka's theorizing should start from the principle that advanced modal reasoning has its roots in commonsense intuitions. It is proposed that the naturalist can rely on the assumption of uniformity: the same set of basic principles is used in reasoning about actual and counterfactual dependencies - modal cognition is conservative. In the most primitive cases the difference between a model of an actual situation and of (...)
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  15.  20
    Scott Atran, Douglas I. Medin & Norbert Ross (2002). Thinking About Biology. Modular Constraints on Categorization and Reasoning in the Everyday Life of Americans, Maya, and Scientists. Mind and Society 3 (2):31-63.
    This essay explores the universal cognitive bases of biological taxonomy and taxonomic inference using cross-cultural experimental work with urbanized Americans and forest-dwelling Maya Indians. A universal, essentialist appreciation of generic species appears as the causal foundation for the taxonomic arrangement of biodiversity, and for inference about the distribution of causally-related properties that underlie biodiversity. Universal folkbiological taxonomy is domain-specific: its structure does not spontaneously or invariably arise in other cognitive domains, like substances, artifacts or persons. It is plausibly an innately-determined (...)
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  16.  17
    Walid S. Saba & Jean-Pierre Corriveau (2001). Plausible Reasoning and the Resolution of Quantifier Scope Ambiguities. Studia Logica 67 (2):271-289.
    Despite overwhelming evidence suggesting that quantifier scope is a phenomenon that must be treated at the pragmatic level, most computational treatments of scope ambiguities have thus far been a collection of syntactically motivated preference rules. This might be in part due to the prevailing wisdom that a commonsense inferencing strategy would require the storage of and reasoning with a vast amount of background knowledge. In this paper we hope to demonstrate that the challenge in developing a commonsense (...)
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  17.  3
    Andrzej Szalas (2006). Second-Order Reasoning in Description Logics. Journal of Applied Non-Classical Logics 16 (3-4):517-530.
    Description logics refer to a family of formalisms concentrated around concepts, roles and individuals. They belong to the most frequently used knowledge representation formalisms and provide a logical basis to a variety of well known paradigms. The main reasoning tasks considered in the area of description logics are those reducible to subsumption. On the other hand, any knowledge representation system should be equipped with a more advanced reasoning machinery. Therefore in the current paper we make a step towards (...)
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  18. Jerry R. Hobbs & Robert C. Moore (1985). Formal Theories of the Commonsense World.
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  19.  4
    F. Alonso-Amo, J. L. Maté, J. L. Morant & J. Pazos (1992). From Epistemology toGnoseology: Foundations of the Knowledge Industry. [REVIEW] AI and Society 6 (2):140-165.
    In this paper, the foundations for setting up a knowledge industry are laid. Firstly, it is established that this industry constitutes the only way of making use of the huge amounts of knowledge produced as a result of the introduction of the Science-Technology binomial in postindustrial society. Then, the elements which will lead to such an industry are defined, that is, the resources and means. Under the ‘Means’ section, special emphasis is placed on the processes involved, in other words, inference (...)
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  20. Kurt Konolige (1996). What's Happening? Elements of Commonsense Causation. In J. Ezquerro A. Clark (ed.), Philosophy and Cognitive Science: Categories, Consciousness, and Reasoning. Kluwer 197--220.
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  21.  28
    Ronald Fagin (ed.) (2003). Reasoning About Knowledge. MIT Press.
    Reasoning About Knowledge is the first book to provide a general discussion of approaches to reasoning about knowledge and its applications to distributed ...
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  22. Robert W. Batterman (2002). The Devil in the Details: Asymptotic Reasoning in Explanation, Reduction, and Emergence. Oxford University Press.
    Robert Batterman examines a form of scientific reasoning called asymptotic reasoning, arguing that it has important consequences for our understanding of the scientific process as a whole. He maintains that asymptotic reasoning is essential for explaining what physicists call universal behavior. With clarity and rigor, he simplifies complex questions about universal behavior, demonstrating a profound understanding of the underlying structures that ground them. This book introduces a valuable new method that is certain to fill explanatory gaps across (...)
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  23.  45
    Hans Rott (2004). A Counterexample to Six Fundamental Principles of Belief Formation. Synthese 139 (2):225 - 240.
    In recent years there has been a growing consensus that ordinary reasoning does not conform to the laws of classical logic, but is rather nonmonotonic in the sense that conclusions previously drawn may well be removed upon acquiring further information. Even so, rational belief formation has up to now been modelled as conforming to some fundamental principles that are classically valid. The counterexample described in this paper suggests that a number of the most cherished of these principles should not (...)
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  24.  1
    Ronald Prescott Loui, Carlos Ivan Ches~Nevar & Ana Gabriela Maguitman, Logical Models of Argument.
    Logical models of argument formalize commonsense reasoning while taking process and computation seriously. This survey discusses the main ideas which characterize di erent logical models of argument. It presents the formal features of a few main approaches to the modeling of argumentation. We trace the evolution of argumentationfrom the mid-80's, when argumentsystems emerged as an alternative to nonmonotonic formalisms based on classical logic, to the present, as argument is embedded in di erent complex systems for real-world applications, and (...)
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  25. E. Thomas Lawson (2005). A New Look at the Science-and-Religion Dialogue. Zygon 40 (3):555-564.
    Cognitive science is beginning to make a contribution to the science-and-religion dialogue by its claims about the nature of both scientific and religious knowledge and the practices such knowledge informs. Of particular importance is the distinction between folk knowledge and abstract theoretical knowledge leading to a distinction between folk science and folk religion on the one hand and the reflective, theoretical, abstract form of thought that characterizes both advanced scientific thought and sophisticated theological reasoning on the other. Both folk (...)
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  26. Colin Howson & Peter Urbach (1993). Scientific Reasoning: The Bayesian Approach. Open Court.
  27.  41
    John F. Horty (1994). Moral Dilemmas and Nonmonotonic Logic. Journal of Philosophical Logic 23 (1):35 - 65.
    From a philosophical standpoint, the work presented here is based on van Fraassen [26]. The bulk of that paper is organized around a series of arguments against the assumption, built into standard deontic logic, that moral dilemmas are impossible; and van Fraassen only briefly sketches his alternative approach. His paper ends with the conclusion that “the problem of possibly irresolvable moral conflict reveals serious flaws in the philosophical and semantic foundations of ‘orthodox’ deontic logic, but also suggests a rich set (...)
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  28.  24
    Dov M. Gabbay & Andrzej Szałas (2007). Second-Order Quantifier Elimination in Higher-Order Contexts with Applications to the Semantical Analysis of Conditionals. Studia Logica 87 (1):37 - 50.
    Second-order quantifier elimination in the context of classical logic emerged as a powerful technique in many applications, including the correspondence theory, relational databases, deductive and knowledge databases, knowledge representation, commonsense reasoning and approximate reasoning. In the current paper we first generalize the result of Nonnengart and Szałas [17] by allowing second-order variables to appear within higher-order contexts. Then we focus on a semantical analysis of conditionals, using the introduced technique and Gabbay’s semantics provided in [10] and substantially (...)
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  29.  21
    Michael Anderson, Logic, Self-Awareness and Self-Improvement: The Metacognitive Loop Andthe Problem of Brittleness.
    This essay describes a general approach to building perturbation-tolerant autonomous systems, based on the conviction that artificial agents should be able to notice when something is amiss, assess the anomaly, and guide a solution into place. This basic strategy of self-guided learning is termed the metacognitive loop; it involves the system monitoring, reasoning about, and, when necessary, altering its own decision-making components. This paper (a) argues that equipping agents with a metacognitive loop can help to overcome the brittleness problem, (...)
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  30.  3
    Vladimir Lifschitz, A Modular Action Description Language.
    “Toy worlds” involving actions, such as the blocks world and the Missionaries and Cannibals puzzle, are often used by researchers in the areas of commonsense reasoning and planning to illustrate and test their ideas. We would like to create a database of generalpurpose knowledge about actions that encodes common features of many action domains of this kind, in the same way as abstract algebra and topology represent common features of specific number systems. This paper is a report (...)
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  31.  79
    Mark Sprevak (2005). The Frame Problem and the Treatment of Prediction. In L. Magnani & R. Dossena (eds.), Computing, Philosophy and Cognition. 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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  32.  12
    James T. Cushing (1990). Is Scientific Methodology Interestingly Atemporal? British Journal for the Philosophy of Science 41 (2):177-194.
    Any division between scientific practice and a metalevel of the methods and goals of science is largely a false dichotomy. Since a priori, foundationist or logicist approaches to normative principles have proven unequal to the task of representing actual scientific practice, methodologies of science must be abstracted from episodes in the history of science. Of course, it is possible that such characteristics could prove universal and constant across various eras. But, case studies show that they are not in anything beyond (...)
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  33.  16
    Douglas W. Maynard & John F. Manzo (1993). On the Sociology of Justice: Theoretical Notes From an Actual Jury Deliberation. Sociological Theory 11 (2):171-193.
    Despite the venerable place that "justice" occupies in social scientific theory and research, little effort has been made to see how members of society themselves define and use the concept when confronted with determining "what has happened" in some social arena, theorizing about why it happened, and deciding what should ensue. We take an ethnomethodological approach to justice, attempting to recover it as a feature of practical activity or a "phenomenon of order." Our analysis involves an actual videotaped jury deliberation. (...)
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  34.  20
    Carlos Iván Chesñevar & Guillermo Ricardo Simari (2007). Modelling Inference in Argumentation Through Labelled Deduction: Formalization and Logical Properties. [REVIEW] Logica Universalis 1 (1):93-124.
    . Artificial Intelligence (AI) has long dealt with the issue of finding a suitable formalization for commonsense reasoning. Defeasible argumentation has proven to be a successful approach in many respects, proving to be a confluence point for many alternative logical frameworks. Different formalisms have been developed, most of them sharing the common notions of argument and warrant. In defeasible argumentation, an argument is a tentative (defeasible) proof for reaching a conclusion. An argument is warranted when it ultimately prevails (...)
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  35.  9
    Evandro Agazzi (2011). One Reason, Several Logics. Manuscrito 34 (1):51-88.
    Humans have used arguments for defending or refuting statements long before the creation of logic as a specialized discipline. This can be interpreted as the fact that an intuitive notion of “logical consequence” or a psychic disposition to articulate reasoning according to this pattern is present in common sense, and logic simply aims at describing and codifying the features of this spontaneous capacity of human reason. It is well known, however, that several arguments easily accepted by common sense are (...)
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  36.  14
    Richmond H. Thomason, Logical Semantics for Causal Constructions.
    Montague’s framework for semantic interpretation has always been less well adapted to the interpretation of words than of syntactic constructions. In the late 1970s, David Dowty addressed this problem, concentrating on the interpretation of tense, aspect, inchoatives, and causatives in an extension of Montague’s Intensional Logic. In this paper I will try to revive this project, conceiving it as part of a larger task aiming at the interpretation of derivational morphology. I will try to identity some obstacles arising in Dowty’s (...)
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  37.  15
    Ron Sun, Intelligence.
    The paper attempts to account for common pattems in commonsense reasoning through integrating rule-based reasoning and similarity-based reasoning as embodied in connectionist models.
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  38.  12
    Gustavo A. Bodanza & Fernando A. Tohmé (2005). Local Logics, Non-Monotonicity and Defeasible Argumentation. Journal of Logic, Language and Information 14 (1):1-12.
    In this paper we present an embedding of abstract argumentation systems into the framework of Barwise and Seligmans logic of information flow. We show that, taking P.M. Dungs characterization of argument systems, a local logic over states of a deliberation may be constructed. In this structure, the key feature of non-monotonicity of commonsense reasoning obtains as the transition from one local logic to another, due to a change in certain background conditions. Each of Dungs extensions of argument systems (...)
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  39.  1
    Vladimir Lifschitz, Why the Monkey Needs the Box: A Serious Look at a Toy Domain.
    “Toy worlds” involving actions, such as the Blocks World and the Monkey and Bananas domain, are often used by researchers in the areas of commonsense reasoning and planning to illustrate and test their ideas. Many of the axioms found in descriptions of these toy worlds are expressions of generalpurpose knowledge, though they are often cast in a form only useful for solving one specific problem and are not faithful representations of general facts that can be used in other (...)
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  40.  1
    Michael Miller & Donald Perlis (1996). Automated Inference in Active Logics. Journal of Applied Non-Classical Logics 6 (1):9-27.
    ABSTRACT Certain problems in commonsense reasoning lend themselves to the use of non-standard formalisms which we call active logics. Among these are problems of objects misidentification. In this paper we describe some technical issues connected with automated inference in active logics, using particular object misidentification problems as illustrations. Control of exponential growth of inferences is a key issue. To control this growth attention is paid to a limited version of an inference rule for negative introspection. We also present (...)
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  41. Cleo Condoravdi & Gerard Renardel de Lavalette (eds.) (2001). Logical Perspectives on Language and Information. Center for the Study of Language and Inf.
    The rapid innovations in digital technology deeply influence views on language and information processing. These exciting developments raise many questions for researchers, and shed new light on old approaches. Researchers are drawn to closely investigate the relation between form and content, the ways that linguistic utterances change information content, and the dynamics of information change. Logic, as an established method of valid argumentation, is a tool that researchers can use to gain insight in these questions of language and computation. In (...)
     
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  42. Gabriele Kern-Isberner & Wilhelm Rödder (2006). Editorial. Logic Journal of the Igpl 14 (3):409-411.
    This special issue “Inferences and Information Processing in a Conditional Framework“ is dedicated to conditionals as central objects for inferencing and information processing. It presents selected revised papers of the Workshop on Conditionals, Information, and Inference, CII'04, held in Ulm, Germany, co-located with the German national conference on AI, KI'2004.Conditional statements If A then B carry a very special kind of information that can not be captured by interpreting them as material implications. Roughly speaking, the premise, A, provides a context (...)
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  43. Kazimierz Trzęsicki (2006). Wkład logików polskich w światową informatykę. Filozofia Nauki 3.
    The position of Polish informatics, as well in research as in didactic, has its roots in achievements of Polish mathematicians of Warsaw School and logicians of Lvov-Warsaw School. Jan Lukasiewicz is considered in the world of computer science as the most famous Polish logician. The parenthesis-free notation, invented by him, is known as PN (Polish Notation) and RPN (Reverse Polish Notation). Lukasiewicz created many-valued logic as a separate subject. The idea of multi-valueness is applied to hardware design (many-valued or fuzzy (...)
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  44. Michał Tyburski (2009). Cyrkumskrypcja: formalizacja rozumowania niemonotonicznego w logice drugiego rzędu. Filozofia Nauki 1.
    We discuss circumscription, a logical formalization of non-monotonic reasoning, introduced by John McCarthy and Vladimir Lifschitz. First section contains presentation of assumptions of logic-based artificial intelligence, problem of non-monotonicity in commonsense reasoning and informal formulation of circumscription. In section two, a formal definition of circumscription is given. The idea of circumscription is discussed from syntactic and semantic point of view. Theoretical investigations are supplemented with examples. In section three, methods of computing circumscription are discussed. Section four contains (...)
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  45.  57
    Antti Kauppinen (forthcoming). Practical Reasoning. In Daniel Star (ed.), Oxford Handbook of Reasons and Normativity. Oxford University Press
    This chapter presents two contemporary pictures of practical reasoning. According to the Rule-Guidance Conception, roughly, practical reasoning is a rule-guided operation of acquiring (or retaining or giving up) intentions so as to meet synchronic requirements of rationality. According to the Reasons-Responsiveness Conception, practical reasoning is a process of responding to reasons we take ourselves to have, and its standards of correctness derive from what we objectively have reason to do, if things are as we suppose them to (...)
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  46. Jonathan St B. T. Evans (ed.) (1989). Bias in Human Reasoning Causes and Consequences. Monograph Collection (Matt - Pseudo).
    This book represents the first major attempt by any author to provide an integrated account of the evidence for bias in human reasoning across a wide range of disparate psychological literatures. The topics discussed involve both deductive and inductive reasoning as well as statistical judgement and inference. In addition, the author proposes a general theoretical approach to the explanations of bias and considers the practical implications for real world decision making. The theoretical stance of the book is based (...)
     
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  47.  96
    Conor McHugh & Jonathan Way (2016). What is Good Reasoning? Philosophy and Phenomenological Research 92 (3).
    What makes the difference between good and bad reasoning? In this paper we defend a novel account of good reasoning—both theoretical and practical—according to which it preserves fittingness or correctness: good reasoning is reasoning which is such as to take you from fitting attitudes to further fitting attitudes, other things equal. This account, we argue, is preferable to two others that feature in the recent literature. The first, which has been made prominent (...)
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  48. Keith E. Stanovich & Richard F. West (2000). Individual Differences in Reasoning: Implications for the Rationality Debate? Behavioral and Brain Sciences 23 (5):645-665.
    Much research in the last two decades has demonstrated that human responses deviate from the performance deemed normative according to various models of decision making and rational judgment (e.g., the basic axioms of utility theory). This gap between the normative and the descriptive can be interpreted as indicating systematic irrationalities in human cognition. However, four alternative interpretations preserve the assumption that human behavior and cognition is largely rational. These posit that the gap is due to (1) performance errors, (2) computational (...)
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  49.  53
    Hans Rott (2001). Change, Choice and Inference: A Study of Belief Revision and Nonmonotonic Reasoning. Oxford University Press.
    Change, Choice and Inference develops logical theories that are necessary both for the understanding of adaptable human reasoning and for the design of intelligent systems. The book shows that reasoning processes - the drawing on inferences and changing one's beliefs - can be viewed as belonging to the realm of practical reason by embedding logical theories into the broader context of the theory of rational choice. The book unifies lively and significant strands of research in logic, (...)
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  50. Jonathan Way (2015). Reasons as Premises of Good Reasoning. Pacific Philosophical Quarterly 96 (3).
    Many philosophers have been attracted to the view that reasons are premises of good reasoning – that reasons to φ are premises of good reasoning towards φ-ing. However, while this reasoning view is indeed attractive, it faces a problem accommodating outweighed reasons. In this article, I argue that the standard solution to this problem is unsuccessful and propose an alternative, which draws on the idea that good patterns of reasoning can be defeasible. I conclude by drawing (...)
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