| 期刊全称 | AI-ML for Decision and Risk Analysis | | 期刊简称 | Challenges and Oppor | | 影响因子2023 | Louis Anthony Cox Jr. | | 视频video | | | 发行地址 | 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 | | 学科分类 | International Series in Operations Research & Management Science | | 图书封面 |  | | 影响因子 | .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.. | | Pindex | Book 2023 |
The information of publication is updating
|
|
发表于 2025-3-21 19:57:37
