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No matter how irrefutable it may seem, evidence is often a matter of interpretation. Incomplete, inconclusive, imprecise, or vague, it is nonetheless the basis of myriad everyday conclusions and decisions. In this authoritative work, David A. Schum develops a general theory of evidence as it is understood and applied across a broad range of disciplines and practical undertakings. Synthesizing insights from law, philosophy and logic, probability, semiotics, artificial intelligence, psychology, and history, Schum provides a detailed examination of the various properties and uses of evidence and the evaluative skills evidence requires. Along with the evidential subtleties of probabilistic reasoning, Schum also explores the processes by which evidence is generated or discovered and looks at the intellectual and practical underpinnings of probabilistic reasoning. It is a useful resource for students, researchers, and practitioners of every discipline concerned with evidence and its inferential use.

Probabilities --- Evidence --- Inference

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Probability theory

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This extensively revised second edition is a rigorous introduction to the construction and criticism of arguments about questions of fact, and to the marshalling and evaluation of evidence at all stages of litigation. It covers the principles underlying the logic of proof; the uses and dangers of story-telling; standards for decision and the relationship between probabilities and proof; the chart method and other methods of analyzing and ordering evidence in fact-investigation, in preparing for trial, and in connection with other important decisions in legal processes and in criminal investigation and intelligence analysis. Most of the chapters in this new edition have been rewritten; the treatment of fact investigation, probabilities and narrative has been extended; and new examples and exercises have been added. Designed as a flexible tool for undergraduate and postgraduate courses on evidence and proof, students, practitioners and teachers alike will find this book challenging but rewarding.

Evidence (Law) --- Study and teaching --- Law --- General and Others --- Evidence (Law) - United States. --- Evidence (Law) - Study and teaching - United States. --- Extrinsic evidence --- Parol evidence --- Trial evidence --- Actions and defenses --- Judicial process --- Trial practice --- Estoppel

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This book presents a significant advancement in the theory and practice of knowledge engineering, the discipline concerned with the development of systems that use expert knowledge and reasoning to solve complex problems. It covers the main stages in the development of a knowledge-based system: understanding the application domain, modeling problem solving in that domain, developing the ontology and the reasoning rules, and testing the system. The book focuses on a special class of systems - learning assistants for evidence-based reasoning that learn complex problem solving expertise directly from human experts, support experts and non-experts in problem solving and decision making, and teach their problem solving expertise to students. A powerful learning agent shell, Disciple-EBR, is included with the book, enabling students, practitioners, and researchers to rapidly develop learning assistants in a wide variety of domains that require evidence-based reasoning, including intelligence analysis, cyber security, law, forensics, medicine, and education.

Expert systems (Computer science) --- Knowledge, Theory of --- Computational learning theory. --- A priori --- Knowledge-based systems (Computer science) --- Systems, Expert (Computer science) --- Artificial intelligence --- Computer systems --- Soft computing --- Apriori --- Logic --- Reasoning --- Machine learning --- Epistemology --- Theory of knowledge --- Philosophy --- Psychology --- Data processing.

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Decision making --- Prise de décision --- Congrès