Heuristics Probability And Casuality
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Heuristics Probability And Casuality
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Author : Rina Dechter
language : en
Publisher:
Release Date : 2010
Heuristics Probability And Casuality written by Rina Dechter and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.
The field of Artificial Intelligence has changed a great deal since the 80s, and arguably no one has played a larger role in that change than Judea Pearl. Judea Pearl's work made probability the prevailing language of modern AI and, perhaps more significantly, it placed the elaboration of crisp and meaningful models, and of effective computational mechanisms, at the center of AI research. This book is a collection of articles in honor of Judea Pearl, written by close colleagues and former students. Its three main parts, heuristics, probabilistic reasoning, and causality, correspond to the titles of the three ground-breaking books authored by Judea, and are followed by a section of short reminiscences. In this volume, leading authors look at the state of the art in the fields of heuristic, probabilistic, and causal reasoning, in light of Judea's seminal contributors. The authors list include Blai Bonet, Eric Hansen, Robert Holte, Jonathan Schaeffer, Ariel Felner, Richard Korf, Austin Parker, Dana Nau, V. S. Subrahmanian, Hector Geffner, Ira Pohl, Adnan Darwiche, Thomas Dean, Rina Dechter, Bozhena Bidyuk, Robert Matescu, Emma Rollon, Michael I. Jordan, Michael Kearns, Daphne Koller, Brian Milch, Stuart Russell, Azaria Paz, David Poole, Ingrid Zukerman, Carlos Brito, Philip Dawid, Felix Elwert, Christopher Winship, Michael Gelfond, Nelson Rushton, Moises Goldszmidt, Sander Greenland, Joseph Y. Halpern, Christopher Hitchcock, David Heckerman, Ross Shachter, Vladimir Lifschitz, Thomas Richardson, James Robins, Yoav Shoham, Peter Spirtes, Clark Glymour, Richard Scheines, Robert Tillman, Wolfgang Spohn, Jian Tian, Ilya Shpitser, Nils Nilsson, Edward T. Purcell, and David Spiegelhalter.
Probabilistic And Causal Inference
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Author : Hector Geffner
language : en
Publisher: Morgan & Claypool
Release Date : 2022-03-10
Probabilistic And Causal Inference written by Hector Geffner and has been published by Morgan & Claypool this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-10 with Computers categories.
Professor Judea Pearl won the 2011 Turing Award “for fundamental contributions to artificial intelligence through the development of a calculus for probabilistic and causal reasoning.” This book contains the original articles that led to the award, as well as other seminal works, divided into four parts: heuristic search, probabilistic reasoning, causality, first period (1988–2001), and causality, recent period (2002–2020). Each of these parts starts with an introduction written by Judea Pearl. The volume also contains original, contributed articles by leading researchers that analyze, extend, or assess the influence of Pearl’s work in different fields: from AI, Machine Learning, and Statistics to Cognitive Science, Philosophy, and the Social Sciences. The first part of the volume includes a biography, a transcript of his Turing Award Lecture, two interviews, and a selected bibliography annotated by him.
Causality
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Author : Judea Pearl
language : en
Publisher: Cambridge University Press
Release Date : 2009-09-14
Causality written by Judea Pearl and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-14 with Computers categories.
Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence ...
Judgment Under Uncertainty
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Author : Daniel Kahneman
language : en
Publisher: Cambridge University Press
Release Date : 1982-04-30
Judgment Under Uncertainty written by Daniel Kahneman and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982-04-30 with Psychology categories.
Thirty-five chapters describe various judgmental heuristics and the biases they produce, not only in laboratory experiments, but in important social, medical, and political situations as well. Most review multiple studies or entire subareas rather than describing single experimental studies.
Simplicity And Complexity Preferences In Causal Explanation
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Author : Samuel Johnson
language : en
Publisher:
Release Date : 2018
Simplicity And Complexity Preferences In Causal Explanation written by Samuel Johnson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
People often prefer simple to complex explanations because they generally have higher prior probability. However, simpler explanations are not always normatively superior because they often do not account for the data as well as complex explanations. How do people negotiate this trade-off between prior probability (favoring simple explanations) and goodness-of-fit (favoring complex explanations)? Here, we argue that people use opponent heuristics to simplify this problem--that people use simplicity as a cue to prior probability but complexity as a cue to goodness-of-fit. Study 1 finds direct evidence for this claim. In subsequent studies, we examine factors that lead one or the other heuristic to predominate in a given context. Studies 2 and 3 find that people have a stronger simplicity preference in deterministic rather than stochastic contexts, while Studies 4 and 5 find that people have a stronger simplicity preference for physical rather than social causal systems, suggesting that people use abstract expectations about causal texture to modulate their explanatory inferences. Together, we argue that these cues and contextual moderators act as powerful constraints that can help to specify the otherwise ill-defined problem of what distributions to use in Bayesian hypothesis comparison.
Probability And Causality
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Author : J.H. Fetzer
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Probability And Causality written by J.H. Fetzer and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
The contributions to this special collection concern issues and problems discussed in or related to the work of Wesley C. Salmon. Salmon has long been noted for his important work in the philosophy of science, which has included research on the interpretation of probability, the nature of explanation, the character of reasoning, the justification of induction, the structure of space/time and the paradoxes of Zeno, to mention only some of the most prominent. During a time of increasing preoccupation with historical and sociological approaches to under standing science (which characterize scientific developments as though they could be adequately analysed from the perspective of political movements, even mistaking the phenomena of conversion for the rational appraisal of scientific theories), Salmon has remained stead fastly devoted to isolating and justifying those normative standards distinguishing science from non-science - especially through the vindi cation of general principles of scientific procedure and the validation of specific examples of scientific theories - without which science itself cannot be (even remotely) adequately understood. In this respect, Salmon exemplifies and strengthens a splendid tradi tion whose most remarkable representatives include Hans Reichenbach, Rudolf Carnap and Carl G. Hempel, all of whom exerted a profound influence upon his own development.
Causality Probability And Time
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Author : Samantha Kleinberg
language : en
Publisher: Cambridge University Press
Release Date : 2013
Causality Probability And Time written by Samantha Kleinberg and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Computers categories.
Presents a new approach to causal inference and explanation, addressing both the timing and complexity of relationships.
Probabilistic Causality
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Author : Ellery Eells
language : en
Publisher: Cambridge University Press
Release Date : 1991-03-29
Probabilistic Causality written by Ellery Eells and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991-03-29 with Business & Economics categories.
In this important first book in the series Cambridge Studies in Probability, Induction and Decision Theory, Ellery Eells explores and refines current philosophical conceptions of probabilistic causality. In a probabilistic theory of causation, causes increase the probability of their effects rather than necessitate their effects in the ways traditional deterministic theories have specified. Philosophical interest in this subject arises from attempts to understand population sciences as well as indeterminism in physics. Taking into account issues involving spurious correlation, probabilistic causal interaction, disjunctive causal factors, and temporal ideas, Professor Eells advances the analysis of what it is for one factor to be a positive causal factor for another. A salient feature of the book is a new theory of token level probabilistic causation in which the evolution of the probability of a later event from an earlier event is central.
Probability And Causality
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Author : J.H. Fetzer
language : en
Publisher: Springer
Release Date : 1987-12-31
Probability And Causality written by J.H. Fetzer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987-12-31 with Science categories.
Reasoning With Probabilistic And Deterministic Graphical Models
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Author : Rina Dechter
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2013-12-01
Reasoning With Probabilistic And Deterministic Graphical Models written by Rina Dechter and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-01 with Computers categories.
Graphical models (e.g., Bayesian and constraint networks, influence diagrams, and Markov decision processes) have become a central paradigm for knowledge representation and reasoning in both artificial intelligence and computer science in general. These models are used to perform many reasoning tasks, such as scheduling, planning and learning, diagnosis and prediction, design, hardware and software verification, and bioinformatics. These problems can be stated as the formal tasks of constraint satisfaction and satisfiability, combinatorial optimization, and probabilistic inference. It is well known that the tasks are computationally hard, but research during the past three decades has yielded a variety of principles and techniques that significantly advanced the state of the art. In this book we provide comprehensive coverage of the primary exact algorithms for reasoning with such models. The main feature exploited by the algorithms is the model's graph. We present inference-based, message-passing schemes (e.g., variable-elimination) and search-based, conditioning schemes (e.g., cycle-cutset conditioning and AND/OR search). Each class possesses distinguished characteristics and in particular has different time vs. space behavior. We emphasize the dependence of both schemes on few graph parameters such as the treewidth, cycle-cutset, and (the pseudo-tree) height. We believe the principles outlined here would serve well in moving forward to approximation and anytime-based schemes. The target audience of this book is researchers and students in the artificial intelligence and machine learning area, and beyond.