Overview
- Highlights recent advances in decision-making and risk analysis
- Elaborates the benefit of modern computational techniques for dealing with realistic complexities
- Explains challenges and opportunities of normative decision theory under current decision-making environments
Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 345)
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About this book
This book explains and illustrates recent developments and advances in decision-making and risk analysis. It demonstrates how artificial intelligence (AI) and machine learning (ML) have not only benefitted from classical decision analysis concepts such as expected utility maximization but have also contributed to making normative decision theory more useful by forcing it to confront realistic complexities. These include skill acquisition, uncertain and time-consuming implementation of intended actions, open-world uncertainties about what might happen next and what consequences actions can have, and learning to cope effectively with uncertain and changing environments. The result is a more robust and implementable technology for AI/ML-assisted decision-making.
The book is intended to inform a wide audience in related applied areas and to provide a fun and stimulating resource for students, researchers, and academics in data science and AI-ML, decision analysis, and other closely linked academic fields. It will also appeal to managers, analysts, decision-makers, and policymakers in financial, health and safety, environmental, business, engineering, and security risk management.
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Keywords
Table of contents (13 chapters)
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Front Matter
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Fundamental Challenges for Practical Decision Theory
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Front Matter
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Public Health Applications
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Front Matter
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Back Matter
Authors and Affiliations
About the author
Louis Anthony Cox Jr. is a Professor of Business Analytics at the University of Colorado, USA; Chief Digital Intelligence Officer at Entanglement, Inc.; and President of Cox Associates, a Denver-based applied research company specializing in artificial intelligence and machine learning; health, safety, and environmental risk analysis; epidemiology; policy analytics; data science; and operations research. Dr. Cox is Editor-in-Chief of Risk Analysis: An International Journal. He is a member of the National Academy of Engineering, a Fellow of the Institute for Operations Research and Management Science (INFORMS), and a Fellow of the Society for Risk Analysis (SRA). He has authored and co-authored over 200 journal articles and numerous books and chapters in these fields. He holds over a dozen US patents on applications of artificial intelligence, signal processing, statistics, and operations research in telecommunications. His current research interestsinclude computational statistical methods for causal inference in public health risk analysis, data mining, and advanced analytics for risk management, business, and public policy applications.
Bibliographic Information
Book Title: AI-ML for Decision and Risk Analysis
Book Subtitle: Challenges and Opportunities for Normative Decision Theory
Authors: Louis Anthony Cox Jr.
Series Title: International Series in Operations Research & Management Science
DOI: https://doi.org/10.1007/978-3-031-32013-2
Publisher: Springer Cham
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-32012-5Published: 06 July 2023
Softcover ISBN: 978-3-031-32015-6Published: 06 July 2024
eBook ISBN: 978-3-031-32013-2Published: 05 July 2023
Series ISSN: 0884-8289
Series E-ISSN: 2214-7934
Edition Number: 1
Number of Pages: XXIII, 433
Number of Illustrations: 1 b/w illustrations
Topics: Operations Research/Decision Theory, Risk Management, Machine Learning, Artificial Intelligence, Statistics and Computing/Statistics Programs, Probability Theory and Stochastic Processes