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Naive Decision Making

Author: T. W. Körner

Publisher: Cambridge University Press

Published: 2008-10-16

Total Pages: 375

ISBN-13: 1139473565

How should one choose the best restaurant to eat in? Can one really make money at gambling? Or predict the future? Naive Decision Making presents the mathematical basis for making decisions where the outcome may be uncertain or the interests of others have to taken into consideration. Professor Körner takes the reader on an enjoyable journey through many aspects of mathematical decision making, with pithy observations, anecdotes and quotations. Topics include probability, statistics, Arrow's theorem, Game Theory and Nash equilibrium. Readers will also gain a great deal of insight into mathematics in general and the role it can play within society. Intended for those with elementary calculus, this book is ideal as a supplementary text for undergraduate courses in probability, game theory and decision making. Engaging and intriguing, it will also appeal to all those of a mathematical mind. To aid understanding, many exercises are included, with solutions available online.

Naive Decision Making

Author: T. W. Ko ̈rner

Publisher:

Published: 2014-05-14

Total Pages: 391

ISBN-13: 9780511438417

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Takes readers on an enjoyable journey through many aspects of mathematical decision making; the only prerequisite is elementary calculus.

Naive Decision Making

Author: T. W. Körner

Publisher: Cambridge University Press

Published: 2008-10-16

Total Pages: 400

ISBN-13: 9780521516167

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How should one choose the best restaurant to eat in? Can one really make money at gambling? Or predict the future? Naive Decision Making presents the mathematical basis for making everyday decisions, which my often be based on very little or uncertain data. Professor Körner takes the reader on an enjoyable journey through many aspects of mathematical decision making, with relatable observations, anecdotes and quotations. Topics include probability, statistics, Arrow's theorem, Game Theory and Nash equilibrium. Readers will also gain a great deal of insight into mathematics in general and the role it can play within society. Suitable for those with elementary calculus, this book is ideal as a supplementary text for undergraduate courses in probability, game theory and decision making. Engaging and intriguing, it will also appeal to all those of a mathematical mind. To aid understanding, many exercises are included, with solutions available online.

Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making

Author: Cengiz Kahraman

Publisher: Springer

Published: 2019-07-05

Total Pages: 1392

ISBN-13: 3030237567

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This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23–25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, France, Poland, Mexico, Bulgaria, Algeria, Pakistan, Australia, Lebanon, and Czech Republic.

Decision Making

Author: Ray Crozier

Publisher: Routledge

Published: 2002-09-11

Total Pages: 282

ISBN-13: 1134726775

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This book offers an exciting new collection of recent research on the actual processes that humans use when making decisions in their everyday lives and in business situations. The contributors use cognitive psychological techniques to break down the constituent processes and set them in their social context. The contributors are from many different countries and draw upon a wide range of techniques, making this book a valuable resource to cognitive psychologists in applied settings, economists and managers.

Knowledge Elicitation of Recognition-primed Decision Making

Author: Gary A. Klein

Publisher:

Published: 1988

Total Pages: 68

ISBN-13:

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"A Critical Decision Method (CDM) has been developed for knowledge elicitation. The CDM, an extension of the critical incident technique, includes protocol analysis and memory recall tasks to study cognitive performance. A set of probes is employed to trace the development of situation assessment during critical incidents, and to determine the decision strategies used. The outputs of the method include inventories of the critical cues, graphic portrayals of the situation assessment process, and categorization of the decision strategies. Thus far, the method has been used with a variety of decisions and appears especially well suited to studying cognitive performance in naturalistic settings. It also appears valuable for addressing the highly skilled decision maker, and for eliciting the analytical and perceptual bases of proficient performance. Applications have been made for training, decision support systems, and the development and evaluation of knowledge based systems." -- Abstract.

Lecture Notes in Computational Intelligence and Decision Making

Author: Volodymyr Lytvynenko

Publisher: Springer

Published: 2019-07-23

Total Pages: 715

ISBN-13: 3030264742

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Information and computer technologies for data analysis and processing in various fields of data mining and machine learning generates the conditions for increasing the effectiveness of information processing by making it faster and more accurate. The book includes 49 scientific papers presenting the latest research in the fields of data mining, machine learning and decision-making. Divided into three sections: “Analysis and Modeling of Complex Systems and Processes”; “Theoretical and Applied Aspects of Decision-Making Systems”; and “Computational Intelligence and Inductive Modeling”, the book is of interest to scientists and developers in the field.

Decision Making under Uncertainty

Author: Kerstin Preuschoff

Publisher: Frontiers Media SA

Published: 2015-06-16

Total Pages: 144

ISBN-13: 2889194663

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Most decisions in life are based on incomplete information and have uncertain consequences. To successfully cope with real-life situations, the nervous system has to estimate, represent and eventually resolve uncertainty at various levels. A common tradeoff in such decisions involves those between the magnitude of the expected rewards and the uncertainty of obtaining the rewards. For instance, a decision maker may choose to forgo the high expected rewards of investing in the stock market and settle instead for the lower expected reward and much less uncertainty of a savings account. Little is known about how different forms of uncertainty, such as risk or ambiguity, are processed and learned about and how they are integrated with expected rewards and individual preferences throughout the decision making process. With this Research Topic we aim to provide a deeper and more detailed understanding of the processes behind decision making under uncertainty.

Machine Learning for Decision Makers

Author: Patanjali Kashyap

Publisher: Apress

Published: 2018-01-04

Total Pages: 381

ISBN-13: 1484229886

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Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the relationship of machine learning with IoT, big data, and cognitive and cloud computing to give you an overview of how these modern areas of computing relate to each other. This book introduces a collection of the most important concepts of machine learning and sets them in context with other vital technologies that decision makers need to know about. These concepts span the process from envisioning the problem to applying machine-learning techniques to your particular situation. This discussion also provides an insight to help deploy the results to improve decision-making. The book uses case studies and jargon busting to help you grasp the theory of machine learning quickly. You'll soon gain the big picture of machine learning and how it fits with other cutting-edge IT services. This knowledge will give you confidence in your decisions for the future of your business. What You Will Learn Discover the machine learning, big data, and cloud and cognitive computing technology stack Gain insights into machine learning concepts and practices Understand business and enterprise decision-making using machine learning Absorb machine-learning best practices Who This Book Is For Managers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them.