**Author**: George Pólya

**Publisher:**Princeton University Press

**ISBN:**9780691025100

**Category:**Mathematics

**Page:**225

**View:**7545

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# Search Results for: mathematics-and-plausible-reasoning-volume-ii-patterns-of-plausible-inference-patterns-of-plausible-inference-v-2

**Author**: George Pólya

**Publisher:** Princeton University Press

**ISBN:** 9780691025100

**Category:** Mathematics

**Page:** 225

**View:** 7545

A guide to the practical art of plausible reasoning, this book has relevance in every field of intellectual activity. Professor Polya, a world-famous mathematician from Stanford University, uses mathematics to show how hunches and guesses play an important part in even the most rigorously deductive science. He explains how solutions to problems can be guessed at; good guessing is often more important than rigorous deduction in finding correct solutions. Vol. II, on Patterns of Plausible Inference, attempts to develop a logic of plausibility. What makes some evidence stronger and some weaker? How does one seek evidence that will make a suspected truth more probable? These questions involve philosophy and psychology as well as mathematics.

**Author**: George Pólya

**Publisher:** Princeton University Press

**ISBN:** 9780691025094

**Category:** Mathematics

**Page:** 280

**View:** 2763

A guide to the practical art of plausible reasoning, this book has relevance in every field of intellectual activity. Professor Polya, a world-famous mathematician from Stanford University, uses mathematics to show how hunches and guesses play an important part in even the most rigorously deductive science. He explains how solutions to problems can be guessed at; good guessing is often more important than rigorous deduction in finding correct solutions. Vol. I, on Induction and Analogy in Mathematics, covers a wide variety of mathematical problems, revealing the trains of thought that lead to solutions, pointing out false bypaths, discussing techniques of searching for proofs. Problems and examples challenge curiosity, judgment, and power of invention.
*Networks of Plausible Inference*

**Author**: Judea Pearl

**Publisher:** Elsevier

**ISBN:** 0080514898

**Category:** Computers

**Page:** 552

**View:** 5178

Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
*The Stochastic Analysis of Real-World Signals*

**Author**: David Mumford,Agnès Desolneux

**Publisher:** CRC Press

**ISBN:** 1439865566

**Category:** Mathematics

**Page:** 375

**View:** 2713

Pattern theory is a distinctive approach to the analysis of all forms of real-world signals. At its core is the design of a large variety of probabilistic models whose samples reproduce the look and feel of the real signals, their patterns, and their variability. Bayesian statistical inference then allows you to apply these models in the analysis of new signals. This book treats the mathematical tools, the models themselves, and the computational algorithms for applying statistics to analyze six representative classes of signals of increasing complexity. The book covers patterns in text, sound, and images. Discussions of images include recognizing characters, textures, nature scenes, and human faces. The text includes online access to the materials (data, code, etc.) needed for the exercises.

**Author**: Judea Pearl

**Publisher:** Cambridge University Press

**ISBN:** 1139643983

**Category:** Science

**Page:** N.A

**View:** 4249

Written by one of the preeminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, economics, philosophy, cognitive science, and the health and social sciences. Judea Pearl presents and unifies the probabilistic, manipulative, counterfactual, and structural approaches to causation and devises simple mathematical tools for studying the relationships between causal connections and statistical associations. Cited in more than 2,100 scientific publications, it continues to liberate scientists from the traditional molds of statistical thinking. In this revised edition, Judea Pearl elucidates thorny issues, answers readers' questions, and offers a panoramic view of recent advances in this field of research. Causality will be of interest to students and professionals in a wide variety of fields. Dr Judea Pearl has received the 2011 Rumelhart Prize for his leading research in Artificial Intelligence (AI) and systems from The Cognitive Science Society.

**Author**: Giandomenico Sica

**Publisher:** Polimetrica s.a.s.

**ISBN:** 8876990143

**Category:** Mathematics

**Page:** 351

**View:** 1274

**Author**: Michael R. Matthews

**Publisher:** Springer

**ISBN:** 9400776543

**Category:** Education

**Page:** 2532

**View:** 6214

This inaugural handbook documents the distinctive research field that utilizes history and philosophy in investigation of theoretical, curricular and pedagogical issues in the teaching of science and mathematics. It is contributed to by 130 researchers from 30 countries; it provides a logically structured, fully referenced guide to the ways in which science and mathematics education is, informed by the history and philosophy of these disciplines, as well as by the philosophy of education more generally. The first handbook to cover the field, it lays down a much-needed marker of progress to date and provides a platform for informed and coherent future analysis and research of the subject. The publication comes at a time of heightened worldwide concern over the standard of science and mathematics education, attended by fierce debate over how best to reform curricula and enliven student engagement in the subjects. There is a growing recognition among educators and policy makers that the learning of science must dovetail with learning about science; this handbook is uniquely positioned as a locus for the discussion. The handbook features sections on pedagogical, theoretical, national, and biographical research, setting the literature of each tradition in its historical context. It reminds readers at a crucial juncture that there has been a long and rich tradition of historical and philosophical engagements with science and mathematics teaching, and that lessons can be learnt from these engagements for the resolution of current theoretical, curricular and pedagogical questions that face teachers and administrators. Science educators will be grateful for this unique, encyclopaedic handbook, Gerald Holton, Physics Department, Harvard University This handbook gathers the fruits of over thirty years’ research by a growing international and cosmopolitan community Fabio Bevilacqua, Physics Department, University of Pavia
*The Art of Investigation*

**Author**: A. Gardiner

**Publisher:** Courier Corporation

**ISBN:** 0486452999

**Category:** Mathematics

**Page:** 206

**View:** 6832

The term "mathematics" usually suggests an array of familiar problems with solutions derived from well-known techniques. Discovering Mathematics: The Art of Investigation takes a different approach, exploring how new ideas and chance observations can be pursued, and focusing on how the process invariably leads to interesting questions that would never have otherwise arisen. With puzzles involving coins, postage stamps, and other commonplace items, students are challenged to account for the simple explanations behind perplexing mathematical phenomena. Elementary methods and solutions allow readers to concentrate on the way in which the material is explored, as well as on strategies for answers that aren't immediately obvious. The problems don't require the kind of sophistication that would put them out of reach of ordinary students, but they're sufficiently complex to capture the essential features of mathematical discovery. Complete solutions appear at the end.

**Author**: Kumaraswamy Vela Velupillai

**Publisher:** Routledge

**ISBN:** 1134385455

**Category:** Business & Economics

**Page:** 200

**View:** 9225

Herbert Simon (1916-2001) is mostly celebrated for the theory of bounded rationality and satisficing. This book of essays on Models of Simon tackles these topics that the he broached in a professional career spanning more than 60 years. Expository material on the fundamental concepts he introduced are re-interpreted in terms of the theory of computability. This volume frames the behavioural issues of concern for economists, such as: hierarchy, causality, near-diagonal linear dynamical systems, discovery, the contrasts between the notion of heuristics, and the Church-Turing Thesis of Computability Theory. There is, consistently, an emphasis on the historical origins of the concepts Simon worked with, in emphasising Human Problem Solving and Decision Making – by rational individuals and institutions (like Organizations). The main feature of the results in the book are its emphasis on the procedural aspects of human problem solving, decision making and the remarkable way Simon harnessed many tools of mathematical logic, mathematics, cognitive sciences, economics and econometrics. This long-awaited volume is an important read for those who study economic theory and philosophy, microeconomics and political economy, as well as those interested in the great Herbert Simon’s work.

**Author**: George Pólya,Sam Sloan

**Publisher:** N.A

**ISBN:** 9784871878326

**Category:** Mathematics

**Page:** 218

**View:** 372

"Solving problems," writes Polya, "is a practical art, like swimming, or skiing, or playing the piano: You can learn it only by imitation and practice. This book cannot offer you a magic key that opens all the doors and solves all the problems, but it offers you good examples for imitation and many opportunities for practice: If you wish to learn swimming you have to go into the water and if you wish to become a problem solver you have to solve problems." "In enough cases to allay . . . discouragement over not immediately discovering a solution, Professor Polya masterfully leads the reader down several unproductive paths. At the end of each chapter he provides examples for the render to solve. By means of these carefully selected and arranged problems, many of them directly related to others that precede, and guided by just the right suggestions at just the proper time, the reader's own ability is developed and extended. Solutions to the examples and, in many cases, outlines of procedures for discovering solutions. arc given at the back of the book. With striking promise for effectiveness, the entire book as a unit is one great experience in learning processes for problem solving through participation. The author has captured with great success the implication of his basic premise stated in the preface ..." The Mathematics Teacher
*An Essay for the Design of Computer-Based Modeling Tools*

**Author**: Tony Hürlimann

**Publisher:** Springer Science & Business Media

**ISBN:** 147575793X

**Category:** Mathematics

**Page:** 313

**View:** 4711

Computer-based mathematical modeling - the technique of representing and managing models in machine-readable form - is still in its infancy despite the many powerful mathematical software packages already available which can solve astonishingly complex and large models. On the one hand, using mathematical and logical notation, we can formulate models which cannot be solved by any computer in reasonable time - or which cannot even be solved by any method. On the other hand, we can solve certain classes of much larger models than we can practically handle and manipulate without heavy programming. This is especially true in operations research where it is common to solve models with many thousands of variables. Even today, there are no general modeling tools that accompany the whole modeling process from start to finish, that is to say, from model creation to report writing. This book proposes a framework for computer-based modeling. More precisely, it puts forward a modeling language as a kernel representation for mathematical models. It presents a general specification for modeling tools. The book does not expose any solution methods or algorithms which may be useful in solving models, neither is it a treatise on how to build them. No help is intended here for the modeler by giving practical modeling exercises, although several models will be presented in order to illustrate the framework. Nevertheless, a short introduction to the modeling process is given in order to expound the necessary background for the proposed modeling framework.

**Author**: Harold Jeffreys

**Publisher:** Read Books Ltd

**ISBN:** 1447494784

**Category:** Science

**Page:** 260

**View:** 426

Originally published in 1931. The present work had its beginnings in a series of papers published jointly some years ago by Dr Dorothy Wrinch and myself. Both before and since that time several books purporting to give analyses of the principles of scientific inquiry have appeared, but it seems to me that none of them gives adequate attention to the chief guiding principle of both scientific and everyday knowledge that it is possible to learn from experience and to make inferences from it beyond the data directly known by sensation. Discussions from the philosophical and logical point of view have tended to the conclusion that this principle cannot be justified by logic alone, which is true, and have left it at that. In discussions by physicists, on the other hand, it hardly seems to be noticed that such a principle exists. In the present work the principle is frankly adopted as a primitive postulate and its consequences are developed. It is found to lead to an explanation and a justification of the high probabilities attached in practice to simple quantitative laws, and thereby to a recasting of the processes involved in description. As illustrations of the actual relations of scientific laws to experience it is shown how the sciences of mensuration and dynamics may be developed. I have been stimulated to an interest in the subject myself on account of the fact that in my work in the subjects of cosmogony and geophysics it has habitually been necessary to apply physical laws far beyond their original range of verification in both time and distance, and the problems involved in such extrapolation have therefore always been prominent. This is a high quality digital version of the original title, thus a few of the images may be slightly blurred and difficult to read.

**Author**: Glenn Shafer

**Publisher:** Princeton University Press

**ISBN:** 069110042X

**Category:** Business & Economics

**Page:** 297

**View:** 8739

Both in science and in practical affairs we reason by combining facts only inconclusively supported by evidence. Building on an abstract understanding of this process of combination, this book constructs a new theory of epistemic probability. The theory draws on the work of A. P. Dempster but diverges from Depster's viewpoint by identifying his "lower probabilities" as epistemic probabilities and taking his rule for combining "upper and lower probabilities" as fundamental. The book opens with a critique of the well-known Bayesian theory of epistemic probability. It then proceeds to develop an alternative to the additive set functions and the rule of conditioning of the Bayesian theory: set functions that need only be what Choquet called "monotone of order of infinity." and Dempster's rule for combining such set functions. This rule, together with the idea of "weights of evidence," leads to both an extensive new theory and a better understanding of the Bayesian theory. The book concludes with a brief treatment of statistical inference and a discussion of the limitations of epistemic probability. Appendices contain mathematical proofs, which are relatively elementary and seldom depend on mathematics more advanced that the binomial theorem.

**Author**: David J. C. MacKay

**Publisher:** Cambridge University Press

**ISBN:** 9780521642989

**Category:** Computers

**Page:** 628

**View:** 5916

Fun and exciting textbook on the mathematics underpinning the most dynamic areas of modern science and engineering.

**Author**: N.A

**Publisher:** Elsevier

**ISBN:** 9780080466637

**Category:** Mathematics

**Page:** 1218

**View:** 5947

The papers presented in this volume examine topics of central interest in contemporary philosophy of logic. They include reflections on the nature of logic and its relevance for philosophy today, and explore in depth developments in informal logic and the relation of informal to symbolic logic, mathematical metatheory and the limiting metatheorems, modal logic, many-valued logic, relevance and paraconsistent logic, free logics, extensional v. intensional logics, the logic of fiction, epistemic logic, formal logical and semantic paradoxes, the concept of truth, the formal theory of entailment, objectual and substitutional interpretation of the quantifiers, infinity and domain constraints, the Löwenheim-Skolem theorem and Skolem paradox, vagueness, modal realism v. actualism, counterfactuals and the logic of causation, applications of logic and mathematics to the physical sciences, logically possible worlds and counterpart semantics, and the legacy of Hilbert’s program and logicism. The handbook is meant to be both a compendium of new work in symbolic logic and an authoritative resource for students and researchers, a book to be consulted for specific information about recent developments in logic and to be read with pleasure for its technical acumen and philosophical insights. - Written by leading logicians and philosophers - Comprehensive authoritative coverage of all major areas of contemporary research in symbolic logic - Clear, in-depth expositions of technical detail - Progressive organization from general considerations to informal to symbolic logic to nonclassical logics - Presents current work in symbolic logic within a unified framework - Accessible to students, engaging for experts and professionals - Insightful philosophical discussions of all aspects of logic - Useful bibliographies in every chapter
*The Logic of Science*

**Author**: E. T. Jaynes

**Publisher:** Cambridge University Press

**ISBN:** 1139435167

**Category:** Science

**Page:** N.A

**View:** 2287

The standard rules of probability can be interpreted as uniquely valid principles in logic. In this book, E. T. Jaynes dispels the imaginary distinction between 'probability theory' and 'statistical inference', leaving a logical unity and simplicity, which provides greater technical power and flexibility in applications. This book goes beyond the conventional mathematics of probability theory, viewing the subject in a wider context. New results are discussed, along with applications of probability theory to a wide variety of problems in physics, mathematics, economics, chemistry and biology. It contains many exercises and problems, and is suitable for use as a textbook on graduate level courses involving data analysis. The material is aimed at readers who are already familiar with applied mathematics at an advanced undergraduate level or higher. The book will be of interest to scientists working in any area where inference from incomplete information is necessary.
*With Hints and Solutions*

**Author**: George Polya,Jeremy Kilpatrick

**Publisher:** Courier Corporation

**ISBN:** 048631832X

**Category:** Mathematics

**Page:** 80

**View:** 7294

Based on Stanford University's well-known competitive exam, this excellent mathematics workbook offers students at both high school and college levels a complete set of problems, hints, and solutions. 1974 edition.

**Author**: Association for Computing Machinery

**Publisher:** Assn for Computing Machinery

**ISBN:** N.A

**Category:** Computers

**Page:** 110

**View:** 5325

*Algorithms and Applications*

**Author**: Richard Szeliski

**Publisher:** Springer Science & Business Media

**ISBN:** 9781848829350

**Category:** Computers

**Page:** 812

**View:** 4513

Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques. Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

**Author**: National Research Council,Division of Behavioral and Social Sciences and Education,Center for Education,Committee on Scientific Principles for Education Research

**Publisher:** National Academies Press

**ISBN:** 9780309133098

**Category:** Education

**Page:** 204

**View:** 4128

Researchers, historians, and philosophers of science have debated the nature of scientific research in education for more than 100 years. Recent enthusiasm for "evidence-based" policy and practice in educationâ€"now codified in the federal law that authorizes the bulk of elementary and secondary education programsâ€"have brought a new sense of urgency to understanding the ways in which the basic tenets of science manifest in the study of teaching, learning, and schooling. Scientific Research in Education describes the similarities and differences between scientific inquiry in education and scientific inquiry in other fields and disciplines and provides a number of examples to illustrate these ideas. Its main argument is that all scientific endeavors share a common set of principles, and that each fieldâ€"including education researchâ€"develops a specialization that accounts for the particulars of what is being studied. The book also provides suggestions for how the federal government can best support high-quality scientific research in education.

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