Foundations Of Info Metrics
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Foundations of Info-Metrics
Author: Amos Golan
language: en
Publisher: Oxford University Press
Release Date: 2017-11-07
Info-metrics is the science of modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is at the intersection of information theory, statistical inference, and decision-making under uncertainty. It plays an important role in helping make informed decisions even when there is inadequate or incomplete information because it provides a framework to process available information with minimal reliance on assumptions that cannot be validated. In this pioneering book, Amos Golan, a leader in info-metrics, focuses on unifying information processing, modeling and inference within a single constrained optimization framework. Foundations of Info-Metrics provides an overview of modeling and inference, rather than a problem specific model, and progresses from the simple premise that information is often insufficient to provide a unique answer for decisions we wish to make. Each decision, or solution, is derived from the available input information along with a choice of inferential procedure. The book contains numerous multidisciplinary applications and case studies, which demonstrate the simplicity and generality of the framework in real world settings. Examples include initial diagnosis at an emergency room, optimal dose decisions, election forecasting, network and information aggregation, weather pattern analyses, portfolio allocation, strategy inference for interacting entities, incorporation of prior information, option pricing, and modeling an interacting social system. Graphical representations illustrate how results can be visualized while exercises and problem sets facilitate extensions. This book is this designed to be accessible for researchers, graduate students, and practitioners across the disciplines.
Advances in Info-Metrics
Info-metrics is a framework for modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is an interdisciplinary framework situated at the intersection of information theory, statistical inference, and decision-making under uncertainty. In Advances in Info-Metrics, Min Chen, J. Michael Dunn, Amos Golan, and Aman Ullah bring together a group of thirty experts to expand the study of info-metrics across the sciences and demonstrate how to solve problems using this interdisciplinary framework. Building on the theoretical underpinnings of info-metrics, the volume sheds new light on statistical inference, information, and general problem solving. The book explores the basis of information-theoretic inference and its mathematical and philosophical foundations. It emphasizes the interrelationship between information and inference and includes explanations of model building, theory creation, estimation, prediction, and decision making. Each of the nineteen chapters provides the necessary tools for using the info-metrics framework to solve a problem. The collection covers recent developments in the field, as well as many new cross-disciplinary case studies and examples. Designed to be accessible for researchers, graduate students, and practitioners across disciplines, this book provides a clear, hands-on experience for readers interested in solving problems when presented with incomplete and imperfect information.
Empirical Foundations of Information and Software Science V
Author: Pranas Zunde
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
This is the proceedings of the Sixth Symposium on Empirical Foundations of Information and Software Sciences (EFISS), which was held in Atlanta, Georgia, on October 19-21, 1988. The purpose of the symposia is to explore subjects and methods of scientific inquiry which are of common interest to information and software sciences, and to identify directions of research that would benefit from the mutual interaction of these two disciplines. The main theme of the sixth symposium was modeling in information and software engineering, with emphasis on methods and tools of modeling. The symposium covered topics such as models of individual and organizational users of information systems, methods of selecting appropriate types of models for a given type of users and a given type of tasks, deriving models from records of system usage, modeling system evolution, constructing user and task models for adaptive systems, and models of system architectures. This symposium was sponsored by the School of Information and Computer Science of the Georgia Institute of Technology and by the U.S. Army Institute for Research in Management Information, Communications, and Computer Sciences (AIRMICS). 17le Editors vii CONTENTS 1 I. KEYNOTE ADDRESS ............................................. .