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The Neuroscience and Psychophysiology of Experience-Based Decisions
In experience-based decisions people learn to make decisions by sampling the relevant alternatives and getting feedback. The study of experience-based decisions has recently revealed some robust regularities that differ from how people make decisions based on descriptions. For example, people were found to underweight small probability events in experience-based decisions, while overweighting them in decisions based on descriptions (i.e. where the participants have full information about the outcome distributions but no feedback). This is now commonly referred to as the description-experience gap. In parallel to the recent advancement in Decision Science, neuroscientists have for a long whil...
Developments on Experimental Economics
This volume on experimental economics offers both new research grounds and a bird’s eye view on the field. In the first part, leading experimental economists, among them Vernon S. Smith and Daniel Friedman, give inspiring insights into their view on the general development of this field. In the second part, selected short papers by researchers from various disciplines present new ideas and concepts to solving problems in the real world.
Information Sampling and Adaptive Cognition
This book proposes that environmental information samples are biased and cognitive processes are not.
Predicting Human Decision-Making
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.
Bounded Rationality
In a complex and uncertain world, humans and animals make decisions under the constraints of limited knowledge, resources, and time. Yet models of rational decision making in economics, cognitive science, biology, and other fields largely ignore these real constraints and instead assume agents with perfect information and unlimited time. About forty years ago, Herbert Simon challenged this view with his notion of "bounded rationality." Today, bounded rationality has become a fashionable term used for disparate views of reasoning. This book promotes bounded rationality as the key to understanding how real people make decisions. Using the concept of an "adaptive toolbox," a repertoire of fast ...
Signals
Brian Skyrms offers a fascinating demonstration of how fundamental signals are to our world. He uses various scientific tools to investigate how meaning and communication develop. Signals operate in networks of senders and receivers at all levels of life, transmitting and processing information. That is how humans and animals think and interact.
Behavioral Game Theory
Game theory, the formalized study of strategy, began in the 1940s by asking how emotionless geniuses should play games, but ignored until recently how average people with emotions and limited foresight actually play games. This book marks the first substantial and authoritative effort to close this gap. Colin Camerer, one of the field's leading figures, uses psychological principles and hundreds of experiments to develop mathematical theories of reciprocity, limited strategizing, and learning, which help predict what real people and companies do in strategic situations. Unifying a wealth of information from ongoing studies in strategic behavior, he takes the experimental science of behaviora...
Experimental Business Research
Experimental Business Research includes papers that were presented at the First Asian Conference on Experimental Business Research held at the Hong Kong University of Science and Technology (HKUST), on December 7-10, 1999. The conference was organized by the Center for Experimental Business Research (cEBR) at the HKUST. The papers presented at the conference and a few others that were solicited especially for this volume contain original research on individual and interactive decision behavior in various branches of business research including, but not limited to, economics, marketing, management, finance, and accounting. Experimental Business Research is suitable as a secondary text for a graduate level course, and as a reference for researchers and practitioners in industry.
Decision Making: Neural and Behavioural Approaches
This well-established international series examines major areas of basic and clinical research within neuroscience, as well as emerging and promising subfields.This volume explores interdisciplinary research on decision making taking a neural and behavioural approach - Leading authors review the state-of-the-art in their field of investigation, and provide their views and perspectives for future research - Chapters are extensively referenced to provide readers with a comprehensive list of resources on the topics covered - All chapters include comprehensive background information and are written in a clear form that is also accessible to the non-specialist
Sampling in Judgment and Decision Making
An exploration of how statistical sampling principles impose theoretical constraints and enable novel insights on judgments and decisions.
