Predicting Human Decision-Making

Predicting Human Decision-Making PDF

Author: Ariel Geib

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 134

ISBN-13: 3031015789

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Human decision-making often transcends our formal models of "rationality." Designing intelligent agents that interact proficiently with people necessitates the modeling of human behavior and the prediction of their decisions. In this book, we explore the task of automatically predicting human decision-making and its use in designing intelligent human-aware automated computer systems of varying natures—from purely conflicting interaction settings (e.g., security and games) to fully cooperative interaction settings (e.g., autonomous driving and personal robotic assistants). We explore the techniques, algorithms, and empirical methodologies for meeting the challenges that arise from the above tasks and illustrate major benefits from the use of these computational solutions in real-world application domains such as security, negotiations, argumentative interactions, voting systems, autonomous driving, and games. The book presents both the traditional and classical methods as well as the most recent and cutting edge advances, providing the reader with a panorama of the challenges and solutions in predicting human decision-making.

Modeling Human and Organizational Behavior

Modeling Human and Organizational Behavior PDF

Author: Panel on Modeling Human Behavior and Command Decision Making: Representations for Military Simulations

Publisher: National Academies Press

Published: 1998-08-14

Total Pages: 433

ISBN-13: 0309523893

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Simulations are widely used in the military for training personnel, analyzing proposed equipment, and rehearsing missions, and these simulations need realistic models of human behavior. This book draws together a wide variety of theoretical and applied research in human behavior modeling that can be considered for use in those simulations. It covers behavior at the individual, unit, and command level. At the individual soldier level, the topics covered include attention, learning, memory, decisionmaking, perception, situation awareness, and planning. At the unit level, the focus is on command and control. The book provides short-, medium-, and long-term goals for research and development of more realistic models of human behavior.

Prediction

Prediction PDF

Author: Daniel R. Sarewitz

Publisher:

Published: 2000-04

Total Pages: 434

ISBN-13:

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Based upon ten case studies, Prediction explores how science-based predictions guide policy making and what this means in terms of global warming, biogenetically modifying organisms and polluting the environment with chemicals.

COVID-19: Prediction, Decision-Making, and its Impacts

COVID-19: Prediction, Decision-Making, and its Impacts PDF

Author: K.C. Santosh

Publisher: Springer Nature

Published: 2020-12-11

Total Pages: 137

ISBN-13: 9811596824

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The book aims to outline the issues of AI and COVID-19, involving predictions,medical support decision-making, and possible impact on human life. Starting withmajor COVID-19 issues and challenges, it takes possible AI-based solutions forseveral problems, such as public health surveillance, early (epidemic) prediction,COVID-19 positive case detection, and robotics integration against COVID-19.Beside mathematical modeling, it includes the necessity of changes in innovationsand possible COVID-19 impacts. The book covers a clear understanding of AI-driven tools and techniques, where pattern recognition, anomaly detection, machinelearning, and data analytics are considered. It aims to include the wide range ofaudiences from computer science and engineering to healthcare professionals.

Thinking

Thinking PDF

Author: John Brockman

Publisher: Harper Collins

Published: 2013-10-29

Total Pages: 294

ISBN-13: 0062258567

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Unlock your mind. From the bestselling authors of Thinking, Fast and Slow; The Black Swan; and Stumbling on Happiness comes a cutting-edge exploration of the mysteries of rational thought, decision-making, intuition, morality, willpower, problem-solving, prediction, forecasting, unconscious behavior, and beyond. Edited by John Brockman, publisher of Edge.org ("The world's smartest website"—The Guardian), Thinking presents original ideas by today's leading psychologists, neuroscientists, and philosophers who are radically expanding our understanding of human thought. Contributors include: Daniel Kahneman on the power (and pitfalls) of human intuition and "unconscious" thinking Daniel Gilbert on desire, prediction, and why getting what we want doesn't always make us happy Nassim Nicholas Taleb on the limitations of statistics in guiding decision-making Vilayanur Ramachandran on the scientific underpinnings of human nature Simon Baron-Cohen on the startling effects of testosterone on the brain Daniel C. Dennett on decoding the architecture of the "normal" human mind Sarah-Jayne Blakemore on mental disorders and the crucial developmental phase of adolescence Jonathan Haidt, Sam Harris, and Roy Baumeister on the science of morality, ethics, and the emerging synthesis of evolutionary and biological thinking Gerd Gigerenzer on rationality and what informs our choices

Decision Science: A Human-Oriented Perspective

Decision Science: A Human-Oriented Perspective PDF

Author: George Mengov

Publisher: Springer

Published: 2015-05-15

Total Pages: 170

ISBN-13: 3662471221

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This book offers a new perspective on human decision-making by comparing the established methods in decision science with innovative modelling at the level of neurons and neural interactions. The book presents a new generation of computer models, which can predict with astonishing accuracy individual economic choices when people make them by quick intuition rather than by effort. A vision for a new kind of social science is outlined, whereby neural models of emotion and cognition capture the dynamics of socioeconomic systems and virtual social networks. The exposition is approachable by experts as well as by advanced students. The author is an Associate Professor of Decision Science with a doctorate in Computational Neuroscience, and a former software consultant to banks in the City of London.

Behavioral Decision Theory

Behavioral Decision Theory PDF

Author: Kazuhisa Takemura

Publisher: Springer Nature

Published: 2021-09-29

Total Pages: 389

ISBN-13: 9811654530

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This book is the second edition of Behavioral Decision Theory, published in 2014. The main approach and structure of this book have been retained in the new edition. However, this second edition provides a fresh overview of the idea of behavioral decision theory and related research findings such as theoretical and empirical discoveries of preference formation, time discounting, social interaction, and social decision making. The book covers a wide range from classical to relatively recent major studies concerning behavioral decision theory, which, in brief, is a general term for descriptive theories to explain the psychological knowledge related to people’s decision-making behavior. It is called a theory but is actually a combination of various psychological theories, for which no axiomatic systems—such as those associated with the utility theory widely used in economics—have been established. The utility theory is often limited to qualitative knowledge; however, as the studies of Nobel laureates H. A. Simon, D. Kahneman, and R. Thaler have suggested, the psychological methodology and knowledge of behavioral decision theory have been applied widely in such fields as economics, business administration, and engineering and are expected to become even more useful in the future. Research into people’s decision making represents an important part in those fields, various aspects of which overlap with the scope of behavioral decision theory. This theory is closely related to behavioral economics and behavioral finance, which have come into greater use in recent years. This book will appeal especially to graduate students, advanced undergraduate students, and researchers who are interested in decision-making phenomena.

Utility, Probability, and Human Decision Making

Utility, Probability, and Human Decision Making PDF

Author: D. Wendt

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 408

ISBN-13: 9401018340

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Human decision making involves problems which are being studied with increasing interest and sophistication. They range from controversial political decisions via individual consumer decisions to such simple tasks as signal discriminations. Although it would seem that decisions have to do with choices among available actions of any kind, there is general agreement that decision making research should pertain to choice prob lems which cannot be solved without a predecisional stage of finding choice alternatives, weighing evidence, and judging values. The ultimate objective of scientific research on decision making is two-fold: (a) to develop a theoretically sound technology for the optimal solution of decision problems, and (b) to formulate a descriptive theory of human decision making. The latter may, in tum, protect decision makers from being caught in the traps of their own limitations and biases. Recently, in decision making research the strong emphasis on well defined laboratory tasks is decreasing in favour of more realistic studies in various practical settings. This may well have been caused by a growing awareness of the fact that decision-behaviour is strongly determined by situational factors, which makes it necessary to look into processes of interaction between the decision maker and the relevant task environ ment. Almost inevitably there is a parallel shift of interest towards problems of utility measurement and the evaluation of consequences.

Artificial Intelligence and Knowledge Processing

Artificial Intelligence and Knowledge Processing PDF

Author: Hemachandran K

Publisher: CRC Press

Published: 2023-09-06

Total Pages: 372

ISBN-13: 1000934624

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Artificial Intelligence and Knowledge Processing play a vital role in various automation industries and their functioning in converting traditional industries to AI-based factories. This book acts as a guide and blends the basics of Artificial Intelligence in various domains, which include Machine Learning, Deep Learning, Artificial Neural Networks, and Expert Systems, and extends their application in all sectors. Artificial Intelligence and Knowledge Processing: Improved Decision-Making and Prediction, discusses the designing of new AI algorithms used to convert general applications to AI-based applications. It highlights different Machine Learning and Deep Learning models for various applications used in healthcare and wellness, agriculture, and automobiles. The book offers an overview of the rapidly growing and developing field of AI applications, along with Knowledge of Engineering, and Business Analytics. Real-time case studies are included across several different fields such as Image Processing, Text Mining, Healthcare, Finance, Digital Marketing, and HR Analytics. The book also introduces a statistical background and probabilistic framework to enhance the understanding of continuous distributions. Topics such as Ensemble Models, Deep Learning Models, Artificial Neural Networks, Expert Systems, and Decision-Based Systems round out the offerings of this book. This multi-contributed book is a valuable source for researchers, academics, technologists, industrialists, practitioners, and all those who wish to explore the applications of AI, Knowledge Processing, Deep Learning, and Machine Learning.

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