Discovering Causal Structure: Artificial Intelligence, Philosophy of Science, and Statistical Modeling provides information pertinent to the fundamental aspects of a computer program called TETRAD. This book discusses the version of the TETRAD program, which is designed to assist in the search for causal explanations of statistical data. or alternative models. This text then examines the notion of applying artificial intelligence methods to problems of statistical model specification. Other chapters consider how the TETRAD program can help to find god alternative models where they exist, and how it can help detect the existence of important neglected variables. This book discusses as well the procedures for specifying a model or models to account for non-experimental or quasi-experimental data. The final chapter presents a description of the format of input files and a description of each command. This book is a valuable resource for social scientists and researchers.
The authors address the assumptions and methods that allow us to turn observations into causal knowledge, and use even incomplete causal knowledge in planning and prediction to influence and control our environment. What assumptions and methods allow us to turn observations into causal knowledge, and how can even incomplete causal knowledge be used in planning and prediction to influence and control our environment? In this book Peter Spirtes, Clark Glymour, and Richard Scheines address these questions using the formalism of Bayes networks, with results that have been applied in diverse areas of research in the social, behavioral, and physical sciences. The authors show that although experimental and observational study designs may not always permit the same inferences, they are subject to uniform principles. They axiomatize the connection between causal structure and probabilistic independence, explore several varieties of causal indistinguishability, formulate a theory of manipulation, and develop asymptotically reliable procedures for searching over equivalence classes of causal models, including models of categorical data and structural equation models with and without latent variables. The authors show that the relationship between causality and probability can also help to clarify such diverse topics in statistics as the comparative power of experimentation versus observation, Simpson's paradox, errors in regression models, retrospective versus prospective sampling, and variable selection. The second edition contains a new introduction and an extensive survey of advances and applications that have appeared since the first edition was published in 1993.
Despite the enormous and accelerating worldwide interest in Wagner leading to the bicentenary of his birth in 2013, his prose writings have received scant scholarly attention. Wagner's book-length essay on Beethoven, written to celebrate the centenary of Beethoven's birth in 1870, is really about Wagner himself rather than Beethoven. It is generally regarded as the principal aesthetic statement of the composer's later years, representing a reassessment of the ideas of the earlier Zurich writings, especially Oper und Drama, in the light of the experience gained through the composition of Tristan und Isolde, Die Meistersinger von N rnberg and the greater part of Der Ring des Nibelungen. It contains Wagner's most complete exegesis of his understanding of Schopenhauer's philosophy and its perceived influence on the compositional practice of his later works. The essay also influenced the young Nietzsche. It is an essential text in the teaching of not only Wagnerian thought but also late nineteenth-century musical aesthetics in general. Until now the English reader with no access to the German original has been obliged to work from two Victorian translations. This brand new edition gives the German original and the newly translated English text on facing pages. It comes along with a substantial introduction placing the essay not only within the wider historical and intellectual context of Wagner's later thought but also in the political context of the establishment of the German Empire in the 1870s. The translation is annotated throughout with a full bibliography. Richard Wagner's Beethoven will be indispensable reading for historians and musicologists as well as those interested in Wagner's philosophy and the aesthetics of music. ROGER ALLEN is Fellow and Tutor in Music at St Peter's College, Oxford.
The second edition features: a CD with all of the book's Amos, EQS, and LISREL programs and data sets; new chapters on importing data issues related to data editing and on how to report research; an updated introduction to matrix notation and programs that illustrate how to compute these calculations; many more computer program examples and chapter exercises; and increased coverage of factors that affect correlation, the 4-step approach to SEM and hypothesis testing, significance, power, and sample size issues. The new edition's expanded use of applications make this book ideal for advanced students and researchers in psychology, education, business, health care, political science, sociology, and biology. A basic understanding of correlation is assumed and an understanding of the matrices used in SEM models is encouraged.
The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods. The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding. Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more.
The notion of artificial intelligence (AI) often sparks thoughts of characters from science fiction, such as the Terminator and HAL 9000. While these two artificial entities do not exist, the algorithms of AI have been able to address many real issues, from performing medical diagnoses to navigating difficult terrain to monitoring possible failures
The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book provides background material on probability, statistics, and genetics, and then moves on to discuss Bayesian networks and applications to bioinformatics. Rather than getting bogged down in proofs and algorithms, probabilistic methods used for biological information and Bayesian networks are explained in an accessible way using applications and case studies. The many useful applications of Bayesian networks that have been developed in the past 10 years are discussed. Forming a review of all the significant work in the field that will arguably become the most prevalent method in biological data analysis. - Unique coverage of probabilistic reasoning methods applied to bioinformatics data--those methods that are likely to become the standard analysis tools for bioinformatics. - Shares insights about when and why probabilistic methods can and cannot be used effectively; - Complete review of Bayesian networks and probabilistic methods with a practical approach.
Probabilistic Methods for Financial and Marketing Informatics aims to provide students with insights and a guide explaining how to apply probabilistic reasoning to business problems. Rather than dwelling on rigor, algorithms, and proofs of theorems, the authors concentrate on showing examples and using the software package Netica to represent and solve problems. The book contains unique coverage of probabilistic reasoning topics applied to business problems, including marketing, banking, operations management, and finance. It shares insights about when and why probabilistic methods can and cannot be used effectively. This book is recommended for all R&D professionals and students who are involved with industrial informatics, that is, applying the methodologies of computer science and engineering to business or industry information. This includes computer science and other professionals in the data management and data mining field whose interests are business and marketing information in general, and who want to apply AI and probabilistic methods to their problems in order to better predict how well a product or service will do in a particular market, for instance. Typical fields where this technology is used are in advertising, venture capital decision making, operational risk measurement in any industry, credit scoring, and investment science. - Unique coverage of probabilistic reasoning topics applied to business problems, including marketing, banking, operations management, and finance - Shares insights about when and why probabilistic methods can and cannot be used effectively - Complete review of Bayesian networks and probabilistic methods for those IT professionals new to informatics.
This unique volume contains, in parallel translation, a thousand of the most frequently performed Lieder, both piano-accompanied and orchestral. Composers are arranged alphabetically, with their songs appearing under poet in chronological order of composition - thus allowing the reader to engage in depth with a particular poet and at the same time to follow the composer's development. Richard Stokes, whose work in this field is already widely acclaimed, provides illuminating short essays on each of the fifty composers' approach to Lieder composition, as well as well as notes on all the poets who inspired the songs.The volume is notable for the accuracy and elegance of its translations, and for its fidelity to the German verse: every care has been taken to print the words of the sung text, while adhering to the versification and punctuation of the original poem.Beethoven, Schubert and Schumann, Goethe, Heine and Schiller are among the highlights of a book which illuminates one of the great musical traditions and will be an indispensable handbook for every music lover.
Written for researchers and students in statistics, machine learning, and the biological sciences. This book provides a self-contained introduction to the methodology of Bayesian networks. It offers both elementary tutorials as well as more advanced applications and case studies.
Corry examines the metaphysical presuppositions in the reductive method of explanation. He argues that it makes assumptions about the nature of causal power and causal influence, he outlines implications for traditional philosophical problems, and he presents an integrated metaphysical worldview grounded in the nature of power and influence.
When making decisions, people naturally face uncertainty about the potential consequences of their actions due in part to limits in their capacity to represent, evaluate or deliberate. Nonetheless, they aim to make the best decisions possible. In Decision Theory with a Human Face, Richard Bradley develops new theories of agency and rational decision-making, offering guidance on how 'real' agents who are aware of their bounds should represent the uncertainty they face, how they should revise their opinions as a result of experience and how they should make decisions when lacking full awareness of, or precise opinions on relevant contingencies. He engages with the strengths and flaws of Bayesian reasoning, and presents clear and comprehensive explorations of key issues in decision theory, from belief and desire to semantics and learning. His book draws on philosophy, economics, decision science and psychology, and will appeal to readers in all of these disciplines.
Richard Wagner (1813-1883) zählt zu den herausragendsten Komponisten der Welt überhaupt und gilt aufgrund seiner musikalischen Interpretationen als ein Erneuerer der europäischen Musiklandschaft. Er fühlte eine enge Verbindung zu Ludwig van Beethoven, da eben sein Werk für die Entscheidung verantwortlich war, sich der Musik zuzuwenden. Das vorliegende Werk ist eine Hommage an den deutschen Künstler und erschien zu seinem einhundersten Geburtsjahr 1870. Es handelt sich hierbei um die englische Übersetzung der deutschen Originalfassung.
Enlarged to describe more than a decade of advances in the immunotherapy of allergic diseases and asthma, this Third Edition contains the most recent studies on the mechanisms, manufacture, and standardization of various allergen groups and their utilization in the treatment of allergic diseases-containing 8 new chapters detailing various pharmacoe
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.
Researchers and clinicians relate their experience with immunotherapy using antigens, which has remained important throughout the enormous advances in immunology over the past 30 years. Among the topics are a historical perspective, outdoor and indoor allergens, venoms, the preparation and administration of extracts, and reactions and other adverse effects. Annotation copyrighted by Book News, Inc., Portland, OR
Cause is a problematic concept in social science, as in all fields of knowledge. We organise information in terms of cause and effect to impose order on the world, but this can impede a more sophisticated understanding. In his latest book, Richard Ned Lebow reviews understandings of cause in physics and philosophy and concludes that no formulation is logically defensible and universal in its coverage. This is because cause is not a feature of the world but a cognitive shorthand we use to make sense of it. In practice, causal inference is always rhetorical and must accordingly be judged on grounds of practicality. Lebow offers a new approach - 'inefficient causation' - that is constructivist in its emphasis on the reasons people have for acting as they do, but turns to other approaches to understand the aggregation of their behaviour. This novel approach builds on general understandings and idiosyncratic features of context.
A comprehensive bibliography on all scholarly work that was published on Plato and Socrates during the years 1958-73. The author has sought to include all materials primarily concerned with Socrates and Plato, together with other works which make a contribution to our understanding of the two philosophers.
Richard Barsam has given us as comprehensive a study of the origins and development of the nonfiction mode in motion pictures as we are ever likely to have in one volume. He draws on all the major written sources and many which are little known, and he shares with us many eloquent descriptions of the films themselves, giving us a valuable textbook." --Richard Dyer MacCann "... superb work... " --Historical Journal of Film, Radio, and Television
Explanatory of the history, manners, and customs of the Jews, and neighbouring nations. With An Account Of The Most Remarkable Places And Persons Mentioned In Sacred Scripture.
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