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Author : Håkan Alm
Publisher :
ISBN 13 :
Total Pages : 86 pages
Book Rating : 4.F/5 ( download)
Download or read book Learning of Probabilisitic Inference Tasks written by Håkan Alm and published by . This book was released on 1982 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Daphne Koller
Publisher : MIT Press
ISBN 13 : 0262258358
Total Pages : 1270 pages
Book Rating : 4.2/5 (622 download)
Download or read book Probabilistic Graphical Models written by Daphne Koller and published by MIT Press. This book was released on 2009-07-31 with total page 1270 pages. Available in PDF, EPUB and Kindle. Book excerpt: A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions. Most tasks require a person or an automated system to reason—to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality. Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.
Author : Lars-Erik Warg
Publisher :
ISBN 13 :
Total Pages : 62 pages
Book Rating : 4.:/5 (35 download)
Download or read book The Effect of Task Content on Performance in Probabilistic Inference Tasks written by Lars-Erik Warg and published by . This book was released on 1983 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Thomas Parr
Publisher : MIT Press
ISBN 13 : 0262362287
Total Pages : 313 pages
Book Rating : 4.2/5 (623 download)
Download or read book Active Inference written by Thomas Parr and published by MIT Press. This book was released on 2022-03-29 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first comprehensive treatment of active inference, an integrative perspective on brain, cognition, and behavior used across multiple disciplines. Active inference is a way of understanding sentient behavior—a theory that characterizes perception, planning, and action in terms of probabilistic inference. Developed by theoretical neuroscientist Karl Friston over years of groundbreaking research, active inference provides an integrated perspective on brain, cognition, and behavior that is increasingly used across multiple disciplines including neuroscience, psychology, and philosophy. Active inference puts the action into perception. This book offers the first comprehensive treatment of active inference, covering theory, applications, and cognitive domains. Active inference is a “first principles” approach to understanding behavior and the brain, framed in terms of a single imperative to minimize free energy. The book emphasizes the implications of the free energy principle for understanding how the brain works. It first introduces active inference both conceptually and formally, contextualizing it within current theories of cognition. It then provides specific examples of computational models that use active inference to explain such cognitive phenomena as perception, attention, memory, and planning.
Author : Karl Friston
Publisher : Frontiers Media SA
ISBN 13 : 2889711285
Total Pages : 172 pages
Book Rating : 4.8/5 (897 download)
Download or read book Probabilistic Perspectives on Brain (dys)Function written by Karl Friston and published by Frontiers Media SA. This book was released on 2021-08-02 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Richard W. Morris
Publisher : Academic Press
ISBN 13 : 0128120991
Total Pages : 486 pages
Book Rating : 4.1/5 (281 download)
Download or read book Goal-Directed Decision Making written by Richard W. Morris and published by Academic Press. This book was released on 2018-08-23 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Goal-Directed Decision Making: Computations and Neural Circuits examines the role of goal-directed choice. It begins with an examination of the computations performed by associated circuits, but then moves on to in-depth examinations on how goal-directed learning interacts with other forms of choice and response selection. This is the only book that embraces the multidisciplinary nature of this area of decision-making, integrating our knowledge of goal-directed decision-making from basic, computational, clinical, and ethology research into a single resource that is invaluable for neuroscientists, psychologists and computer scientists alike. The book presents discussions on the broader field of decision-making and how it has expanded to incorporate ideas related to flexible behaviors, such as cognitive control, economic choice, and Bayesian inference, as well as the influences that motivation, context and cues have on behavior and decision-making. - Details the neural circuits functionally involved in goal-directed decision-making and the computations these circuits perform - Discusses changes in goal-directed decision-making spurred by development and disorders, and within real-world applications, including social contexts and addiction - Synthesizes neuroscience, psychology and computer science research to offer a unique perspective on the central and emerging issues in goal-directed decision-making
Author : Pijush Samui
Publisher : Butterworth-Heinemann
ISBN 13 : 0128165464
Total Pages : 592 pages
Book Rating : 4.1/5 (281 download)
Download or read book Handbook of Probabilistic Models written by Pijush Samui and published by Butterworth-Heinemann. This book was released on 2019-10-05 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Probabilistic Models carefully examines the application of advanced probabilistic models in conventional engineering fields. In this comprehensive handbook, practitioners, researchers and scientists will find detailed explanations of technical concepts, applications of the proposed methods, and the respective scientific approaches needed to solve the problem. This book provides an interdisciplinary approach that creates advanced probabilistic models for engineering fields, ranging from conventional fields of mechanical engineering and civil engineering, to electronics, electrical, earth sciences, climate, agriculture, water resource, mathematical sciences and computer sciences. Specific topics covered include minimax probability machine regression, stochastic finite element method, relevance vector machine, logistic regression, Monte Carlo simulations, random matrix, Gaussian process regression, Kalman filter, stochastic optimization, maximum likelihood, Bayesian inference, Bayesian update, kriging, copula-statistical models, and more. - Explains the application of advanced probabilistic models encompassing multidisciplinary research - Applies probabilistic modeling to emerging areas in engineering - Provides an interdisciplinary approach to probabilistic models and their applications, thus solving a wide range of practical problems
Author :
Publisher :
ISBN 13 :
Total Pages : 726 pages
Book Rating : 4.:/5 (319 download)
Download or read book Umeå Psychological Reports written by and published by . This book was released on 1976 with total page 726 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Judea Pearl
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781507894293
Total Pages : 0 pages
Book Rating : 4.8/5 (942 download)
Download or read book An Introduction to Causal Inference written by Judea Pearl and published by Createspace Independent Publishing Platform. This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that underly all causal inferences, the languages used in formulating those assumptions, the conditional nature of all causal and counterfactual claims, and the methods that have been developed for the assessment of such claims. These advances are illustrated using a general theory of causation based on the Structural Causal Model (SCM) described in Pearl (2000a), which subsumes and unifies other approaches to causation, and provides a coherent mathematical foundation for the analysis of causes and counterfactuals. In particular, the paper surveys the development of mathematical tools for inferring (from a combination of data and assumptions) answers to three types of causal queries: (1) queries about the effects of potential interventions, (also called "causal effects" or "policy evaluation") (2) queries about probabilities of counterfactuals, (including assessment of "regret," "attribution" or "causes of effects") and (3) queries about direct and indirect effects (also known as "mediation"). Finally, the paper defines the formal and conceptual relationships between the structural and potential-outcome frameworks and presents tools for a symbiotic analysis that uses the strong features of both. The tools are demonstrated in the analyses of mediation, causes of effects, and probabilities of causation. -- p. 1.
Author : Suzanna Becker
Publisher : MIT Press
ISBN 13 : 9780262025508
Total Pages : 1738 pages
Book Rating : 4.0/5 (255 download)
Download or read book Advances in Neural Information Processing Systems 15 written by Suzanna Becker and published by MIT Press. This book was released on 2003 with total page 1738 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of the 2002 Neural Information Processing Systems Conference.
Author : Mykel J. Kochenderfer
Publisher : MIT Press
ISBN 13 : 0262331713
Total Pages : 350 pages
Book Rating : 4.2/5 (623 download)
Download or read book Decision Making Under Uncertainty written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2015-07-24 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.
Author : David J. C. MacKay
Publisher : Cambridge University Press
ISBN 13 : 9780521642989
Total Pages : 694 pages
Book Rating : 4.6/5 (429 download)
Download or read book Information Theory, Inference and Learning Algorithms written by David J. C. MacKay and published by Cambridge University Press. This book was released on 2003-09-25 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.
Author : Claudia d’Amato
Publisher : Springer
ISBN 13 : 3030003388
Total Pages : 248 pages
Book Rating : 4.0/5 (3 download)
Download or read book Reasoning Web. Learning, Uncertainty, Streaming, and Scalability written by Claudia d’Amato and published by Springer. This book was released on 2018-09-14 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains lecture notes of the 14th Reasoning Web Summer School (RW 2018), held in Esch-sur-Alzette, Luxembourg, in September 2018. The research areas of Semantic Web, Linked Data, and Knowledge Graphs have recently received a lot of attention in academia and industry. Since its inception in 2001, the Semantic Web has aimed at enriching the existing Web with meta-data and processing methods, so as to provide Web-based systems with intelligent capabilities such as context awareness and decision support. The Semantic Web vision has been driving many community efforts which have invested a lot of resources in developing vocabularies and ontologies for annotating their resources semantically. Besides ontologies, rules have long been a central part of the Semantic Web framework and are available as one of its fundamental representation tools, with logic serving as a unifying foundation. Linked Data is a related research area which studies how one can make RDF data available on the Web and interconnect it with other data with the aim of increasing its value for everybody. Knowledge Graphs have been shown useful not only for Web search (as demonstrated by Google, Bing, etc.) but also in many application domains.
Author : Mike Oaksford
Publisher : Oxford University Press
ISBN 13 : 0198524498
Total Pages : 342 pages
Book Rating : 4.1/5 (985 download)
Download or read book Bayesian Rationality written by Mike Oaksford and published by Oxford University Press. This book was released on 2007-02-22 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: For almost 2,500 years, the Western concept of what is to be human has been dominated by the idea that the mind is the seat of reason - humans are, almost by definition, the rational animal. In this text a more radical suggestion for explaining these puzzling aspects of human reasoning is put forward.
Author : Kenji Doya
Publisher : MIT Press
ISBN 13 : 026204238X
Total Pages : 341 pages
Book Rating : 4.2/5 (62 download)
Download or read book Bayesian Brain written by Kenji Doya and published by MIT Press. This book was released on 2007 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: Experimental and theoretical neuroscientists use Bayesian approaches to analyze the brain mechanisms of perception, decision-making, and motor control.
Author : organizational behavior and human performance
Publisher :
ISBN 13 :
Total Pages : 496 pages
Book Rating : 4./5 ( download)
Download or read book ORGANIZATIONAL BEHAVIOR AND HUMAN PERFORMANCE written by organizational behavior and human performance and published by . This book was released on 1979 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Frank H. Knight
Publisher : Cosimo, Inc.
ISBN 13 : 1602060053
Total Pages : 401 pages
Book Rating : 4.6/5 (2 download)
Download or read book Risk, Uncertainty and Profit written by Frank H. Knight and published by Cosimo, Inc.. This book was released on 2006-11-01 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timeless classic of economic theory that remains fascinating and pertinent today, this is Frank Knight's famous explanation of why perfect competition cannot eliminate profits, the important differences between "risk" and "uncertainty," and the vital role of the entrepreneur in profitmaking. Based on Knight's PhD dissertation, this 1921 work, balancing theory with fact to come to stunning insights, is a distinct pleasure to read. FRANK H. KNIGHT (1885-1972) is considered by some the greatest American scholar of economics of the 20th century. An economics professor at the University of Chicago from 1927 until 1955, he was one of the founders of the Chicago school of economics, which influenced Milton Friedman and George Stigler.
