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Causality

Gebonden Engels 2009 9780521895606
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Samenvatting

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.

Specificaties

ISBN13:9780521895606
Taal:Engels
Bindwijze:gebonden
Aantal pagina's:484
Druk:2
Verschijningsdatum:14-9-2009

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Over Judea Pearl

Judea Pearl is een wereldberoemde computerwetenschapper en filosoof, bekend door zijn grensverleggende werk binnen de kunstmatige intelligentie en het ontwikkelen van Bayesiaanse netwerken (voor de liefhebber). In 2011 won hij de Turing Award, de grootste en belangrijkste prijs in de informatica, daarnaast heeft zijn werk vele andere prijzen gewonnen. Hij is voorzitter van de Daniel Pearl Foundation.

Andere boeken door Judea Pearl

Inhoudsopgave

1. Introduction to probabilities, graphs, and causal models; 2. A theory of inferred causation; 3. Causal diagrams and the identification of causal effects; 4. Actions, plans, and direct effects; 5. Causality and structural models in social science and economics; 6. Simpson's paradox, confounding, and collapsibility; 7. The logic of structure-based counterfactuals; 8. Imperfect experiments: bounding effects and counterfactuals; 9. Probability of causation: interpretation and identification; 10. The actual cause.

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