This book describes new techniques for making decisions in situations with uncertainty and new applications of decision-making techniques.
The main emphasis is on situations when it is difficult to decrease uncertainty. For example, it is very difficult to accurately predict human economic behavior, so in economics, it is very important to take this uncertainty into account when making decisions. Other areas where it is difficult to decrease uncertainty are geosciences and teaching. The book analyzes the general problem of decision making and shows how its results can be applied to economics, geosciences, and teaching. Since all these applications involve computing, the book also shows how these results can be applied to computing, including deep learning and quantum computing.
The book is recommended to researchers, practitioners, and students who want to learn more about decision making under uncertainty—and who want to work on remaining challenges.
Содержание
Introduction.- (Rational) Individual Decision Making: Main Ideas.- (Rational) Group Decision Making: General Formulas and a New Simplified Derivation of These Formulas.- How We Can Control Group Decision Making By Modifying the Proposed Options.- The Fact That We Can Only Have Approximate Estimates Explains Why Buying and Selling Prices Are Different.- The “No Trade Theorem” Paradox.- People Make Decisions Based on Clusters Containing Actual Values.- When Revolutions Succeed.- How People Combine Utility Values.- Biased Perception of Time.- Few-Parametric Spatial Models and How They Explain Bhutan Landscape Anomaly.- Dynamic Triggering of Earthquakes.- Applications to Computing: Representing Functions in Quantum.- and Reversible Computing.
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