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Evidential Reasoning

In G. Bongiovanni, Don Postema, A. Rotolo, G. Sartor, C. Valentini & D. Walton, Handbook in Legal Reasoning and Argumentation. Dordrecht, Netherland: Springer. pp. 447-493 (2011)

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  1. (1 other version)Scientific Explanation and the Causal Structure of the World.Wesley C. Salmon - 1984 - Princeton University Press.
    The philosophical theory of scientific explanation proposed here involves a radically new treatment of causality that accords with the pervasively statistical character of contemporary science. Wesley C. Salmon describes three fundamental conceptions of scientific explanation--the epistemic, modal, and ontic. He argues that the prevailing view is untenable and that the modal conception is scientifically out-dated. Significantly revising aspects of his earlier work, he defends a causal/mechanical theory that is a version of the ontic conception. Professor Salmon's theory furnishes a robust (...)
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  • (1 other version)Logical foundations of probability.Rudolf Carnap - 1950 - Chicago]: Chicago University of Chicago Press.
    APA PsycNET abstract: This is the first volume of a two-volume work on Probability and Induction. Because the writer holds that probability logic is identical with inductive logic, this work is devoted to philosophical problems concerning the nature of probability and inductive reasoning. The author rejects a statistical frequency basis for probability in favor of a logical relation between two statements or propositions. Probability "is the degree of confirmation of a hypothesis (or conclusion) on the basis of some given evidence (...)
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  • The structure of empirical knowledge.Laurence BonJour - 1985 - Cambridge: Harvard University Press.
    1 Knowledge and Justification This book is an investigation of one central problem which arises in the attempt to give a philosophical account of empirical ...
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  • Inference to the Best Explanation.Peter Lipton - 1991 - London and New York: Routledge.
    How do we go about weighing evidence, testing hypotheses, and making inferences? According to the model of _Inference to the Best Explanation_, we work out what to infer from the evidence by thinking about what would actually explain that evidence, and we take the ability of a hypothesis to explain the evidence as a sign that the hypothesis is correct. In _Inference to the Best Explanation_, Peter Lipton gives this important and influential idea the development and assessment it deserves. The (...)
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  • Bayesian Epistemology.Luc Bovens & Stephan Hartmann - 2003 - Oxford: Oxford University Press. Edited by Stephan Hartmann.
    Probabilistic models have much to offer to philosophy. We continually receive information from a variety of sources: from our senses, from witnesses, from scientific instruments. When considering whether we should believe this information, we assess whether the sources are independent, how reliable they are, and how plausible and coherent the information is. Bovens and Hartmann provide a systematic Bayesian account of these features of reasoning. Simple Bayesian Networks allow us to model alternative assumptions about the nature of the information sources. (...)
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  • Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.Judea Pearl - 1988 - Morgan Kaufmann.
    The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
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  • Argumentation schemes.Douglas Walton, Chris Reed & Fabrizio Macagno - 2008 - New York: Cambridge University Press. Edited by Chris Reed & Fabrizio Macagno.
    This book provides a systematic analysis of many common argumentation schemes and a compendium of 96 schemes. The study of these schemes, or forms of argument that capture stereotypical patterns of human reasoning, is at the core of argumentation research. Surveying all aspects of argumentation schemes from the ground up, the book takes the reader from the elementary exposition in the first chapter to the latest state of the art in the research efforts to formalize and classify the schemes, outlined (...)
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  • (1 other version)Studies in the logic of explanation.Carl Gustav Hempel & Paul Oppenheim - 1948 - Philosophy of Science 15 (2):135-175.
    To explain the phenomena in the world of our experience, to answer the question “why?” rather than only the question “what?”, is one of the foremost objectives of all rational inquiry; and especially, scientific research in its various branches strives to go beyond a mere description of its subject matter by providing an explanation of the phenomena it investigates. While there is rather general agreement about this chief objective of science, there exists considerable difference of opinion as to the function (...)
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  • The probable and the provable.Laurence Jonathan Cohen - 1977 - Oxford: Clarendon Press.
    The book was planned and written as a single, sustained argument. But earlier versions of a few parts of it have appeared separately. The object of this book is both to establish the existence of the paradoxes, and also to describe a non-Pascalian concept of probability in terms of which one can analyse the structure of forensic proof without giving rise to such typical signs of theoretical misfit. Neither the complementational principle for negation nor the multiplicative principle for conjunction applies (...)
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  • Argumentation Schemes.Douglas Walton, Christopher Reed & Fabrizio Macagno - 2008 - Cambridge and New York: Cambridge University Press. Edited by Chris Reed & Fabrizio Macagno.
    This book provides a systematic analysis of many common argumentation schemes and a compendium of 96 schemes. The study of these schemes, or forms of argument that capture stereotypical patterns of human reasoning, is at the core of argumentation research. Surveying all aspects of argumentation schemes from the ground up, the book takes the reader from the elementary exposition in the first chapter to the latest state of the art in the research efforts to formalize and classify the schemes, outlined (...)
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  • (1 other version)Logical Foundations of Probability.Rudolf Carnap - 1950 - Mind 62 (245):86-99.
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  • Explanation and scientific understanding.Michael Friedman - 1974 - Journal of Philosophy 71 (1):5-19.
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  • (1 other version)The Uses of Argument.Stephen E. Toulmin - 1958 - Philosophy 34 (130):244-245.
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  • (1 other version)Cognitive Carpentry: A Blueprint for how to Build a Person.John L. Pollock - 1995 - MIT Press.
    "A sequel to Pollock's How to Build a Person, this volume builds upon that theoretical groundwork for the implementation of rationality through artificial ...
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  • On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games.Phan Minh Dung - 1995 - Artificial Intelligence 77 (2):321-357.
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  • (1 other version)Studies in the Logic of Explanation.Carl Hempel & Paul Oppenheim - 1948 - Journal of Symbolic Logic 14 (2):133-133.
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  • Defeasible Reasoning.John L. Pollock - 1987 - Cognitive Science 11 (4):481-518.
    There was a long tradition in philosophy according to which good reasoning had to be deductively valid. However, that tradition began to be questioned in the 1960’s, and is now thoroughly discredited. What caused its downfall was the recognition that many familiar kinds of reasoning are not deductively valid, but clearly confer justification on their conclusions. Here are some simple examples.
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  • Gorillas in our midst: Sustained inattentional blindness for dynamic events.Daniel J. Simons & Christopher F. Chabris - 1999 - Perception 28 (9):1059-1074.
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  • Scientific Explanation and the Causal Structure of the World.Ronald N. Giere - 1988 - Philosophical Review 97 (3):444.
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  • Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.J. Pearl, F. Bacchus, P. Spirtes, C. Glymour & R. Scheines - 1988 - Synthese 104 (1):161-176.
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  • Explanatory coherence (plus commentary).Paul Thagard - 1989 - Behavioral and Brain Sciences 12 (3):435-467.
    This target article presents a new computational theory of explanatory coherence that applies to the acceptance and rejection of scientific hypotheses as well as to reasoning in everyday life, The theory consists of seven principles that establish relations of local coherence between a hypothesis and other propositions. A hypothesis coheres with propositions that it explains, or that explain it, or that participate with it in explaining other propositions, or that offer analogous explanations. Propositions are incoherent with each other if they (...)
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  • Dialectics and the macrostructure of arguments: a theory of argument structure.James B. Freeman - 1991 - Berlin ; New York: Foris Publications.
    Chapter The Need for a Theory of Argument Structure. THE STANDARD APPROACH The approach to argument diagramming which we call standard was originated, ...
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  • The plurality of bayesian measures of confirmation and the problem of measure sensitivity.Branden Fitelson - 1999 - Philosophy of Science 66 (3):378.
    Contemporary Bayesian confirmation theorists measure degree of (incremental) confirmation using a variety of non-equivalent relevance measures. As a result, a great many of the arguments surrounding quantitative Bayesian confirmation theory are implicitly sensitive to choice of measure of confirmation. Such arguments are enthymematic, since they tacitly presuppose that certain relevance measures should be used (for various purposes) rather than other relevance measures that have been proposed and defended in the philosophical literature. I present a survey of this pervasive class of (...)
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  • Logical Foundations of Probability.Ernest H. Hutten - 1950 - Journal of Symbolic Logic 16 (3):205-207.
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  • An Introduction to Probability and Inductive Logic.Ian Hacking - 2001 - New York: Cambridge University Press.
    This is an introductory 2001 textbook on probability and induction written by one of the world's foremost philosophers of science. The book has been designed to offer maximal accessibility to the widest range of students and assumes no formal training in elementary symbolic logic. It offers a comprehensive course covering all basic definitions of induction and probability, and considers such topics as decision theory, Bayesianism, frequency ideas, and the philosophical problem of induction. The key features of this book are a (...)
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  • Scientific explanation.James Woodward - 1979 - British Journal for the Philosophy of Science 30 (1):41-67.
    Issues concerning scientific explanation have been a focus of philosophical attention from Pre- Socratic times through the modern period. However, recent discussion really begins with the development of the Deductive-Nomological (DN) model. This model has had many advocates (including Popper 1935, 1959, Braithwaite 1953, Gardiner, 1959, Nagel 1961) but unquestionably the most detailed and influential statement is due to Carl Hempel (Hempel 1942, 1965, and Hempel & Oppenheim 1948). These papers and the reaction to them have structured subsequent discussion concerning (...)
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  • An abstract framework for argumentation with structured arguments.Henry Prakken - 2010 - Argument and Computation 1 (2):93-124.
    An abstract framework for structured arguments is presented, which instantiates Dung's ('On the Acceptability of Arguments and its Fundamental Role in Nonmonotonic Reasoning, Logic Programming, and n- Person Games', Artificial Intelligence , 77, 321-357) abstract argumentation frameworks. Arguments are defined as inference trees formed by applying two kinds of inference rules: strict and defeasible rules. This naturally leads to three ways of attacking an argument: attacking a premise, attacking a conclusion and attacking an inference. To resolve such attacks, preferences may (...)
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  • (1 other version)The Uses of Argument.Frederick L. Will & Stephen Toulmin - 1960 - Philosophical Review 69 (3):399.
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  • Handbook of Argumentation Theory.Frans H. van Eemeren, Bart Garssen, Erik C. W. Krabbe, A. Francisca Snoeck Henkemans, Bart Verheij & Jean H. M. Wagemans - 2014 - Dordrecht, Netherland: Springer.
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  • The Probable and the Provable.Samuel Stoljar - 1981 - Philosophical Review 90 (3):457.
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  • (1 other version)Scientific Explanation and the Causal Structure of the World.Wesley C. Salmon - 1984 - Princeton University Press.
    The philosophical theory of scientific explanation proposed here involves a radically new treatment of causality that accords with the pervasively statistical character of contemporary science. Wesley C. Salmon describes three fundamental conceptions of scientific explanation--the epistemic, modal, and ontic. He argues that the prevailing view (a version of the epistemic conception) is untenable and that the modal conception is scientifically out-dated. Significantly revising aspects of his earlier work, he defends a causal/mechanical theory that is a version of the ontic conception. (...)
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  • (1 other version)The Structure of Empirical Knowledge.Paul K. Moser - 1985 - Philosophy and Phenomenological Research 47 (4):670-673.
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  • Truth, Error, and Criminal Law: An Essay in Legal Epistemology.Larry Laudan - 2006 - Cambridge University Press.
    Beginning with the premise that the principal function of a criminal trial is to find out the truth about a crime, Larry Laudan examines the rules of evidence and procedure that would be appropriate if the discovery of the truth were, as higher courts routinely claim, the overriding aim of the criminal justice system. Laudan mounts a systematic critique of existing rules and procedures that are obstacles to that quest. He also examines issues of error distribution by offering the first (...)
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  • The Evidential Foundations of Probabilistic Reasoning.David A. Schum - 1994 - New York, NY, USA: Wiley-Interscience.
    A detailed treatment regarding the diverse properties and uses of evidence and the judgmental tasks they entail. Examines various processes by which evidence may be developed or discovered. Considers the construction of arguments made in defense of the relevance and credibility of individual items and masses of evidence as well as the task of assessing the inferential force of evidence. Includes over 100 numerical examples to illustrate the workings of diverse probabilistic expressions for the inferential force of evidence and the (...)
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  • An abstract, argumentation-theoretic approach to default reasoning.A. Bondarenko, P. M. Dung, R. A. Kowalski & F. Toni - 1997 - Artificial Intelligence 93 (1-2):63-101.
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  • (1 other version)The Carneades model of argument and burden of proof.Thomas F. Gordon, Henry Prakken & Douglas Walton - 2007 - Artificial Intelligence 171 (10-15):875-896.
    We present a formal, mathematical model of argument structure and evaluation, taking seriously the procedural and dialogical aspects of argumentation. The model applies proof standards to determine the acceptability of statements on an issue-by-issue basis. The model uses different types of premises (ordinary premises, assumptions and exceptions) and information about the dialectical status of statements (stated, questioned, accepted or rejected) to allow the burden of proof to be allocated to the proponent or the respondent, as appropriate, for each premise separately. (...)
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  • Parts and wholes in face recognition.J. W. Tanaka & M. J. Farah - 1991 - Bulletin of the Psychonomic Society 29 (6):520-520.
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  • Solving the Riddle of Coherence.Luc Bovens & Stephan Hartmann - 2003 - Mind 112 (448):601-634.
    A coherent story is a story that fits together well. This notion plays a central role in the coherence theory of justification and has been proposed as a criterion for scientific theory choice. Many attempts have been made to give a probabilistic account of this notion. A proper account of coherence must not start from some partial intuitions, but should pay attention to the role that this notion is supposed to play within a particular context. Coherence is a property of (...)
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  • Reasoning with Rules: An Essay on Legal Reasoning and its Underlying Logic.Jaap Hage - 1996 - Kluwer Academic Publishers.
    Rule-applying legal arguments are traditionally treated as a kind of syllogism. Such a treatment overlooks the fact that legal principles and rules are not statements which describe the world, but rather means by which humans impose structure on the world. Legal rules create legal consequences, they do not describe them. This has consequences for the logic of rule- and principle-applying arguments, the most important of which may be that such arguments are defeasible. This book offers an extensive analysis of the (...)
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  • A mathematical treatment of defeasible reasoning and its implementation.Guillermo R. Simari & Ronald P. Loui - 1992 - Artificial Intelligence 53 (2-3):125-157.
    We present a mathematical approach to defeasible reasoning based on arguments. This approach integrates the notion of specificity introduced by Poole and the theory of warrant presented by Pollock. The main contribution of this paper is a precise, well-defined system which exhibits correct behavior when applied to the benchmark examples in the literature. It aims for usability rather than novelty. We prove that an order relation can be introduced among equivalence classes of arguments under the equi-specificity relation. We also prove (...)
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  • Essai philosophique sur les probabilités.Pierre-Simon Laplace & Maurice Solovine - 1814 - Revue de Métaphysique et de Morale 30 (1):1-2.
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  • Abstract argumentation systems.Gerard A. W. Vreeswijk - 1997 - Artificial Intelligence 90 (1-2):225-279.
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  • A General Structure for Legal Arguments About Evidence Using Bayesian Networks.Norman Fenton, Martin Neil & David A. Lagnado - 2013 - Cognitive Science 37 (1):61-102.
    A Bayesian network (BN) is a graphical model of uncertainty that is especially well suited to legal arguments. It enables us to visualize and model dependencies between different hypotheses and pieces of evidence and to calculate the revised probability beliefs about all uncertain factors when any piece of new evidence is presented. Although BNs have been widely discussed and recently used in the context of legal arguments, there is no systematic, repeatable method for modeling legal arguments as BNs. Hence, where (...)
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  • Foundations of evidence law.Alex Stein - 2005 - New York: Oxford University Press.
    This is the first book to systematically examine the underlying theory of evidence in Anglo-American legal systems. Stein develops a detailed and innovative theory which sets aside the traditional vision of evidence law as facilitating the discovery of the truth. Combining probability theory, epistemology, economic analysis, and moral philosophy, he argues instead that the fundamental purpose of evidence law is to apportion the risk of error in conditions of uncertainty.
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  • Proof with and without probabilities.Bart Verheij - 2017 - Artificial Intelligence and Law 25 (1):127-154.
    Evidential reasoning is hard, and errors can lead to miscarriages of justice with serious consequences. Analytic methods for the correct handling of evidence come in different styles, typically focusing on one of three tools: arguments, scenarios or probabilities. Recent research used Bayesian networks for connecting arguments, scenarios, and probabilities. Well-known issues with Bayesian networks were encountered: More numbers are needed than are available, and there is a risk of misinterpretation of the graph underlying the Bayesian network, for instance as a (...)
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  • Handbook of Logic in Artificial Intelligence and Logic Programming.Dov M. Gabbay, Christopher John Hogger & J. A. Robinson - 1993
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  • A hybrid formal theory of arguments, stories and criminal evidence.Floris J. Bex, Peter J. van Koppen, Henry Prakken & Bart Verheij - 2010 - Artificial Intelligence and Law 18 (2):123-152.
    This paper presents a theory of reasoning with evidence in order to determine the facts in a criminal case. The focus is on the process of proof, in which the facts of the case are determined, rather than on related legal issues, such as the admissibility of evidence. In the literature, two approaches to reasoning with evidence can be distinguished, one argument-based and one story-based. In an argument-based approach to reasoning with evidence, the reasons for and against the occurrence of (...)
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  • Juridical proof and the best explanation.Michael S. Pardo & Ronald J. Allen - 2007 - Law and Philosophy 27 (3):223 - 268.
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  • Reasoning in explanation-based decision making.N. Pennington - 1993 - Cognition 49 (1-2):123-163.
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  • A method for explaining Bayesian networks for legal evidence with scenarios.Charlotte S. Vlek, Henry Prakken, Silja Renooij & Bart Verheij - 2016 - Artificial Intelligence and Law 24 (3):285-324.
    In a criminal trial, a judge or jury needs to reason about what happened based on the available evidence, often including statistical evidence. While a probabilistic approach is suitable for analysing the statistical evidence, a judge or jury may be more inclined to use a narrative or argumentative approach when considering the case as a whole. In this paper we propose a combination of two approaches, combining Bayesian networks with scenarios. Whereas a Bayesian network is a popular tool for analysing (...)
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