Expert Systems and Probabilistic Network Models
Title | Expert Systems and Probabilistic Network Models PDF eBook |
Author | Enrique Castillo |
Publisher | Springer Science & Business Media |
Pages | 612 |
Release | 2012-12-06 |
Genre | Computers |
ISBN | 1461222702 |
Artificial intelligence and expert systems have seen a great deal of research in recent years, much of which has been devoted to methods for incorporating uncertainty into models. This book is devoted to providing a thorough and up-to-date survey of this field for researchers and students.
Probabilistic Networks and Expert Systems
Title | Probabilistic Networks and Expert Systems PDF eBook |
Author | Robert G. Cowell |
Publisher | Springer Science & Business Media |
Pages | 340 |
Release | 2007-07-16 |
Genre | Computers |
ISBN | 9780387718231 |
Probabilistic expert systems are graphical networks which support the modeling of uncertainty and decisions in large complex domains, while retaining ease of calculation. Building on original research by the authors, this book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures, and algorithms. The book will be of interest to researchers in both artificial intelligence and statistics, who desire an introduction to this fascinating and rapidly developing field. The book, winner of the DeGroot Prize 2002, the only book prize in the field of statistics, is new in paperback.
Probabilistic Networks and Expert Systems
Title | Probabilistic Networks and Expert Systems PDF eBook |
Author | Robert G. Cowell |
Publisher | Springer |
Pages | 324 |
Release | 2007-07-25 |
Genre | Mathematics |
ISBN | 9780387718262 |
Probabilistic expert systems are graphical networks which support the modeling of uncertainty and decisions in large complex domains, while retaining ease of calculation. Building on original research by the authors, this book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures, and algorithms. The book will be of interest to researchers in both artificial intelligence and statistics, who desire an introduction to this fascinating and rapidly developing field. The book, winner of the DeGroot Prize 2002, the only book prize in the field of statistics, is new in paperback.
Interactive Collaborative Information Systems
Title | Interactive Collaborative Information Systems PDF eBook |
Author | Robert Babuška |
Publisher | Springer |
Pages | 598 |
Release | 2010-03-22 |
Genre | Technology & Engineering |
ISBN | 3642116884 |
The increasing complexity of our world demands new perspectives on the role of technology in decision making. Human decision making has its li- tations in terms of information-processing capacity. We need new technology to cope with the increasingly complex and information-rich nature of our modern society. This is particularly true for critical environments such as crisis management and tra?c management, where humans need to engage in close collaborations with arti?cial systems to observe and understand the situation and respond in a sensible way. We believe that close collaborations between humans and arti?cial systems will become essential and that the importance of research into Interactive Collaborative Information Systems (ICIS) is self-evident. Developments in information and communication technology have ra- cally changed our working environments. The vast amount of information available nowadays and the wirelessly networked nature of our modern so- ety open up new opportunities to handle di?cult decision-making situations such as computer-supported situation assessment and distributed decision making. To make good use of these new possibilities, we need to update our traditional views on the role and capabilities of information systems. The aim of the Interactive Collaborative Information Systems project is to develop techniques that support humans in complex information en- ronments and that facilitate distributed decision-making capabilities. ICIS emphasizes the importance of building actor-agent communities: close c- laborations between human and arti?cial actors that highlight their comp- mentary capabilities, and in which task distribution is ?exible and adaptive.
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis
Title | Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis PDF eBook |
Author | Uffe B. Kjærulff |
Publisher | Springer Science & Business Media |
Pages | 325 |
Release | 2007-12-20 |
Genre | Computers |
ISBN | 0387741011 |
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence. This book provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended primarily for practitioners, this book does not require sophisticated mathematical skills. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his/her level of understanding.
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis
Title | Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis PDF eBook |
Author | Uffe B. Kjærulff |
Publisher | Springer Science & Business Media |
Pages | 388 |
Release | 2012-11-30 |
Genre | Computers |
ISBN | 1461451043 |
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new sections, in addition to fully-updated examples, tables, figures, and a revised appendix. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his or her level of understanding. The techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined on the basis of numerous courses that the authors have held for practitioners worldwide.
Probabilistic Reasoning in Expert Systems
Title | Probabilistic Reasoning in Expert Systems PDF eBook |
Author | Richard E. Neapolitan |
Publisher | CreateSpace |
Pages | 448 |
Release | 2012-06-01 |
Genre | Computers |
ISBN | 9781477452547 |
This text is a reprint of the seminal 1989 book Probabilistic Reasoning in Expert systems: Theory and Algorithms, which helped serve to create the field we now call Bayesian networks. It introduces the properties of Bayesian networks (called causal networks in the text), discusses algorithms for doing inference in Bayesian networks, covers abductive inference, and provides an introduction to decision analysis. Furthermore, it compares rule-base experts systems to ones based on Bayesian networks, and it introduces the frequentist and Bayesian approaches to probability. Finally, it provides a critique of the maximum entropy formalism. Probabilistic Reasoning in Expert Systems was written from the perspective of a mathematician with the emphasis being on the development of theorems and algorithms. Every effort was made to make the material accessible. There are ample examples throughout the text. This text is important reading for anyone interested in both the fundamentals of Bayesian networks and in the history of how they came to be. It also provides an insightful comparison of the two most prominent approaches to probability.