Download or read book Predicting Human Decision Making written by Ariel Geib and published by Springer Nature. This book was released on 2022-05-31 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Predicting Human Decisions and Actions Finding the Neural Correlates of Decision Making and Actions in Humans written by Omri Perez and published by . This book was released on 2014 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modeling Human and Organizational Behavior written by Panel on Modeling Human Behavior and Command Decision Making: Representations for Military Simulations and published by National Academies Press. This book was released on 1998-08-14 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book An Evaluation of Models of Human Decision Making and Their Implications for Predicting Leisure Choice Behaviour written by and published by . This book was released on 1990 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Prediction written by Daniel R. Sarewitz and published by . This book was released on 2000-04 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Predicting what Reinforcement Learning Will Tell You written by and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book COVID 19 Prediction Decision Making and its Impacts written by K.C. Santosh and published by Springer Nature. This book was released on 2020-12-11 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book The Oxford Handbook of Cognitive Engineering written by John D. Lee and published by Oxford University Press. This book was released on 2013-03-07 with total page 659 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook is the first to provide comprehensive coverage of original state-of-the-science research, analysis, and design of integrated, human-technology systems.
Download or read book On Predicting Stopping Time of Human Sequential Decision making Using Discounted Satisficing Heuristic written by Mounica Devaguptapu and published by . This book was released on 2020 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Human sequential decision-making involves two essential questions: (i) ''what to choose next?'', and (ii) ''when to stop?''. Assuming that the human agents choose an alternative according to their preference order, our goal is to model and learn how human agents choose their stopping time while making sequential decisions. In contrary to traditional assumptions in the literature regarding how humans exhibit satisficing behavior on instantaneous utilities, we assume that humans employ a discounted satisficing heuristic to compute their stopping time, i.e., the human agent stops working if the total accumulated utility goes beyond a dynamic threshold that gets discounted with time. In this thesis, we model the stopping time in 3 scenarios where the payoff of the human worker is assumed as (i) single-attribute utility, (ii) multi-attribute utility with known weights, and (iii) multi-attribute utility with unknown weights. We propose algorithms to estimate the model parameters followed by predicting the stopping time in all three scenarios and present the simulation results to demonstrate the error performance. Simulation results are presented to demonstrate the convergence of prediction error of stopping time, in spite of the fact that model parameters converge to biased estimates. This observation is later justified using an illustrative example to show that there are multiple discounted satisficing models that explain the same stopping time decision. A novel web application is also developed to emulate a crowd-sourcing platform in our lab to capture multi-attribute information regarding the task in order to perform validations of the proposed algorithms on real data"--Abstract, page iii.
Download or read book Utility Probability and Human Decision Making written by D. Wendt and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Decision Making written by Rob Ranyard and published by Psychology Press. This book was released on 1997 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Thinking written by John Brockman and published by Harper Collins. This book was released on 2013-10-29 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Process and Structure in Human Decision Making written by Henry Montgomery and published by . This book was released on 1989-04-24 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fourteen contributors from six countries present recent research results in the study of decision-making processes. They address cognitive and evaluative issues involved in human choice and judgement. Several studies model how decision makers represent and structure information involved in making choices. Others discuss theory, methods, or group decision making.
Download or read book Human Decision Making Behaviors in Engineering and Management A Neuropsychological Perspective written by Pin-Chao Liao and published by Frontiers Media SA. This book was released on 2022-12-05 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modeling and Analysis of Affective Influences on Human Experience Prediction Decision Making and Behavior written by Hyungil Ahn and published by . This book was released on 2010 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Subjective and affective elements are well-known to influence human decision making. This dissertation presents a theoretical and empirical framework on how human decision makers' subjective experience and affective prediction influence their choice behavior under uncertainty, frames and emotions. The framework extends and integrates existing theories of prospect theory (PT) and reinforcement learning (RL), drawing on a growing literature offering the role of affect in decision making and the neural underpinnings of human decision behavior. The proposed Affective-Cognitive (AC) model extends Prospect Theory (PT)- based subjective value functions to model human experienced-utility and predicted-utility functions. The AC model assumes that the shapes (or parameters) of these subjective value functions dynamically vary with the decision makers affective states in sequential decision making. Human decision-making experiments were conducted to empirically infer how people adjust the parameters (i.e., shape and reference point) of their experienced-utility and predicted-utility functions in sequential decision-making situations involving incidental affective states (e.g., anger, fear, economic fear) and task-related confidence. I constructed a new model combining measures to evaluate risk preferences: behavioral choices, selfreported experience self-reported experience, self-reported predicted utility, self-reported confidence. The analysis results show how domain uncertainty, framing, and emotion state of decision makers influence their subjective experience and discriminability, affective prediction, optimal decisions and exploratory regulation. I found empirically that there were significant interaction effects of framing and emotion on risk preferences: negative emotions made people more risk-averse in face of gains. When it comes to losses, anger made people more risk-averse and fear more risk seeking. I also characterized how gender and emotion influence confidence and exploratory choice behavior. The theoretical analysis nicely supports empirical findings from human experiments. The new model provides a theory that better explain and simulate human behavior under uncertainty, frames and emotions.
Download or read book Predicting Human Decision Making written by Ariel Rosenfeld and published by Morgan & Claypool Publishers. This book was released on 2018-01-22 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Artificial Intelligence and Knowledge Processing written by Hemachandran K and published by CRC Press. This book was released on 2023-09-06 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
