001471558 000__ 06840cam\\22006977i\4500
001471558 001__ 1471558
001471558 003__ OCoLC
001471558 005__ 20230908003303.0
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001471558 019__ $$a1389555593
001471558 020__ $$a3031320131$$qelectronic book
001471558 020__ $$a9783031320132$$q(electronic bk.)
001471558 020__ $$z3031320123
001471558 020__ $$z9783031320125
001471558 0247_ $$a10.1007/978-3-031-32013-2$$2doi
001471558 035__ $$aSP(OCoLC)1389612127
001471558 040__ $$aEBLCP$$beng$$erda$$cEBLCP$$dYDX$$dGW5XE$$dYDX$$dN$T
001471558 049__ $$aISEA
001471558 050_4 $$aHD30.23$$b.C68 2023
001471558 08204 $$a658.4030028563$$223/eng/20230714
001471558 1001_ $$aCox, Louis A.,$$cJr.$$q(Louis Anthony),$$d1957-
001471558 24510 $$aAI-ML for decision and risk analysis :$$bchallenges and opportunities for normative decision theory /$$cLouis Anthony Cox Jr.
001471558 264_1 $$aCham, Switzerland :$$bSpringer,$$c[2023]
001471558 300__ $$a1 online resource (443 p.).
001471558 336__ $$atext$$btxt$$2rdacontent
001471558 337__ $$acomputer$$bc$$2rdamedia
001471558 338__ $$aonline resource$$bcr$$2rdacarrier
001471558 4901_ $$aInternational Series in Operations Research and Management Science ;$$vv. 345
001471558 500__ $$aSimulation-Optimization for Continuous, Discrete-Event, and Hybrid Simulation Models
001471558 504__ $$aIncludes bibliographical references and index.
001471558 5050_ $$aIntro -- Preface -- Acknowledgments -- Contents -- Part I: Received Wisdom -- Chapter 1: Rational Decision and Risk Analysis and Irrational Human Behavior -- Introduction -- Extending Classical Decision Analysis (DA) with AI/ML Ideas -- Decision Analysis for Realistically Irrational People -- Two Decision Pathways: Emotions and Reasoning Guide Decisions -- We All Make Predictable Mistakes -- Marketers, Politicians, Journalists, and Others Exploit Our Systematic Mistakes -- People Respond to Incentives and Influences in Groups, Organizations, and Markets
001471558 5058_ $$aMoral Psychology and Norms Improve Cooperative Risk Management -- We Can Learn to Do Better -- The Rise of Behavioral Economics -- Beyond Behavioral Economics and Rational Choice: Behaving Better in a Risky World -- Review of Behave: The Biology of Humans at Our Best and Worst -- 12 Rules for Life: An Antidote to Chaos -- Comments on Behave and 12 Rules -- Review of Morality: Restoring the Common Good in Divided Times -- References -- Chapter 2: Data Analytics and Modeling for Improving Decisions -- Introduction -- Forming More Accurate Beliefs: Superforecasting
001471558 5058_ $$aLearning About the World Through Data Analysis: The Art of Statistics -- Using Models to Interpret Data: The Model Thinker -- Overview of Contents -- Comments on The Model Thinker -- Responding to Change Strategically: Setting Goals and Acting Under Uncertainty -- Using Data to Discover What Works in Disrupting Poverty -- Conceptual Framework: Uncertain Risks and Rewards and Poverty Traps -- Extending and Applying the Framework: How Risk and Perceptions Strengthen Poverty Traps -- Escaping Poverty Traps: Weakly Held Beliefs and Credible Communication
001471558 5058_ $$aHow Can Analysis Help Reduce Health Risks and Poverty? -- References -- Chapter 3: Natural, Artificial, and Social Intelligence for Decision-Making -- Introduction -- Biological Foundations of Thought: Cognitive Neuroscience -- Thinking and Reasoning -- Computational Models of Nondeliberative Thought: Deep Learning (MIT Press, 2019) -- Computational Models of Deliberative Thought: Artificial Intelligence: A Very Short Introduction (Oxford University Press, 201... -- Communities of Knowledge -- Factfulness: Ten Reasons Weŕe Wrong About the World-and Why Things Are Better Than You Think
001471558 5058_ $$aAligning AI-ML and Human Values: The Alignment Problem -- Conclusions -- References -- Part II: Fundamental Challenges for Practical Decision Theory -- Chapter 4: Answerable and Unanswerable Questions in Decision and Risk Analysis -- Introduction: Risk Analysis Questions -- Some Models and Methods for Answering Risk Analysis Questions -- The Simplest Causal Models: Decision Tables and Decision Trees -- Fault Trees, Event Trees, Bayesian Networks (BNs) and Influence Diagrams (IDs) -- Markov Decision Processes (MDPs) and Reinforcement Learning (RL)
001471558 506__ $$aAccess limited to authorized users.
001471558 520__ $$aThis 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.
001471558 588__ $$aDescription based on online resource; title from digital title page (viewed on August 09, 2023).
001471558 650_0 $$aDecision making$$xData processing.
001471558 650_0 $$aRisk assessment$$xData processing.
001471558 650_0 $$aArtificial intelligence.
001471558 650_0 $$aMachine learning.
001471558 655_0 $$aElectronic books.
001471558 77608 $$iPrint version:$$aCox Jr., Louis Anthony$$tAI-ML for Decision and Risk Analysis$$dCham : Springer International Publishing AG,c2023$$z9783031320125
001471558 830_0 $$aInternational series in operations research & management science ;$$vv. 345.
001471558 852__ $$bebk
001471558 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-32013-2$$zOnline Access$$91397441.1
001471558 909CO $$ooai:library.usi.edu:1471558$$pGLOBAL_SET
001471558 980__ $$aBIB
001471558 980__ $$aEBOOK
001471558 982__ $$aEbook
001471558 983__ $$aOnline
001471558 994__ $$a92$$bISE