{"product_id":"bounded-rationality-in-decision-making-under-uncertainty-expert","title":"Bounded Rationality in Decision Making Under Uncertainty - Expert","description":"\u003cp\u003eIn this review of Bounded Rationality in Decision Making Under Uncertainty the authors present a focused, scholarly examination of why human choices often appear irrational. Geared toward researchers and advanced students, the book's single biggest strength is its clear demonstration that limited information processing and coarse-grained representations - what the book calls \u003cstrong\u003egranularity restriction\u003c\/strong\u003e - can produce the biases observed in behavioral studies. The review finds the volume a compact, rigorous bridge between theoretical optimization and the classic Kahneman and Tversky findings, useful for anyone exploring the mathematical foundations of human decision behavior.\u003c\/p\u003e\n\u003ch2\u003eKey Features\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eTheoretical grounding:\u003c\/strong\u003e The book links observed behavioral biases to formal optimization under granularity, clarifying how bounded processing produces systematic deviations from expected-utility predictions.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConnections to classic studies:\u003c\/strong\u003e Drawing on Kahneman and Tversky, it contextualizes empirical anomalies within a coherent decision-theoretic framework that researchers can apply to varied problems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorked examples:\u003c\/strong\u003e Several examples illustrate how optimizing with coarse information leads to common human patterns such as overestimating rare events, making the theory tangible.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eInterdisciplinary appeal:\u003c\/strong\u003e The discussion speaks to computer scientists, AI researchers, and cognitive scientists interested in modelling limited information processing.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConcise presentation:\u003c\/strong\u003e As part of a studies series, the volume focuses tightly on its thesis without lengthy digressions, making it efficient to read for specialists.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eWho It's For\u003c\/h2\u003e\n\u003cp\u003eThe book is best for graduate students, researchers, and professionals in \u003cstrong\u003eAI and decision theory\u003c\/strong\u003e who want a principled account of why humans deviate from idealized rational models. Its formal perspective and reliance on examples make it suitable for readers comfortable with mathematical reasoning and interested in model-driven explanations.\u003c\/p\u003e\n\u003cp\u003eReaders seeking an introductory popular treatment of cognitive biases or a broad survey of behavioral economics should look elsewhere; this volume assumes familiarity with optimization concepts and the basic Kahneman and Tversky literature rather than offering a gentle lay introduction.\u003c\/p\u003e\n\u003ch2\u003ePros \u0026amp; Cons\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003ePros\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eProvides a clear theoretical mechanism linking \u003cstrong\u003egranularity\u003c\/strong\u003e to observed decision biases, useful for model development.\u003c\/li\u003e\n\u003cli\u003eIncorporates classic empirical findings into a formal optimization framework that is directly applicable to research.\u003c\/li\u003e\n\u003cli\u003eWorked examples make abstract points accessible to readers with technical background.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eCons\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eNot aimed at casual readers; the subject assumes some mathematical maturity and familiarity with the founding studies.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eSpecifications\u003c\/h2\u003e\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003eTitle\u003c\/td\u003e\n\u003ctd\u003eBounded Rationality in Decision Making Under Uncertainty\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSeries\u003c\/td\u003e\n\u003ctd\u003eStudies in Systems, Decision and Control, 99\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAuthors\u003c\/td\u003e\n\u003ctd\u003eJoe Lorkowski, Vladik Kreinovich\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFocus\u003c\/td\u003e\n\u003ctd\u003eOptimization under granularity and human decision behavior\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eKey influences\u003c\/td\u003e\n\u003ctd\u003eKahneman and Tversky empirical studies\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAudience\u003c\/td\u003e\n\u003ctd\u003eResearchers and advanced students in AI, decision theory, and cognitive science\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\n\u003ch2\u003eOur Verdict\u003c\/h2\u003e\n\u003cp\u003eFor an audience versed in formal methods, this is a compact and persuasive examination of how bounded information processing produces the biases cataloged by behavioral researchers; it is good value for scholars seeking a rigorous, example-driven explanation that can inform modelling in AI and decision science.\u003c\/p\u003e\n\u003ch2\u003eFrequently Asked Questions\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003eDoes this book explain classic behavioral biases?\u003c\/strong\u003e\u003cbr\u003eYes - it shows how optimization with coarse-grained information reproduces patterns like overestimating rare events identified by Kahneman and Tversky.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eIs advanced math required to read it?\u003c\/strong\u003e\u003cbr\u003eSome familiarity with optimization and formal reasoning is helpful, as the book is aimed at researchers and advanced students, not casual readers.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eWho will benefit most from reading this?\u003c\/strong\u003e\u003cbr\u003eGraduate researchers and practitioners in AI, decision theory, and cognitive modeling will get the most from its theoretical framing and worked examples.\u003c\/p\u003e","brand":"Joe Lorkowski, Vladik Kreinovich","offers":[{"title":"Default Title","offer_id":48613234704603,"sku":"3319872605","price":106.34,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0724\/1043\/1707\/files\/61n8Km67i8L._SL1254.jpg?v=1778408180","url":"https:\/\/gearmusthave.com\/products\/bounded-rationality-in-decision-making-under-uncertainty-expert","provider":"GearMustHave","version":"1.0","type":"link"}