Decision Economics. Designs, Models, and Techniques for Boundedly Rational Decisions, Edgardo Bucciarelli; Shu-Heng Chen; Juan Manuel Co
Автор: Rubinstein Ariel Et Al Название: Models Of Bounded Rationality And Mechanism Design ISBN: 9813141328 ISBN-13(EAN): 9789813141322 Издательство: World Scientific Publishing Цена: 15048.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book brings together the authors' joint papers from over a period of more than twenty years. The collection includes seven papers, each of which presents a novel and rigorous model in Economic Theory.
All of the models are within the domain of implementation and mechanism design theories. These theories attempt to explain how incentive schemes and organizations can be designed with the goal of inducing agents to behave according to the designer's (principal's) objectives. Most of the literature assumes that agents are fully rational. In contrast, the authors inject into each model an element which conflicts with the standard notion of full rationality, demonstrating how such elements can dramatically change the mechanism design problem.
Although all of the models presented in this volume touch on mechanism design issues, it is the formal modeling of bounded rationality that the authors are most interested in. A model of bounded rationality signifies a model that contains a procedural element of reasoning that is not consistent with full rationality. Rather than looking for a canonical model of bounded rationality, the articles introduce a variety of modeling devices that will capture procedural elements not previously considered, and which alter the analysis of the model.
The book is a journey into the modeling of bounded rationality. It is a collection of modeling ideas rather than a general alternative theory of implementation.
This book addresses an intriguing question: are our decisions rational? It explains seemingly irrational human decision-making behavior by taking into account our limited ability to process information. It also shows with several examples that optimization under granularity restriction leads to observed human decision-making. Drawing on the Nobel-prize-winning studies by Kahneman and Tversky, researchers have found many examples of seemingly irrational decisions: e.g., we overestimate the probability of rare events.Our explanation is that since human abilities to process information are limited, we operate not with the exact values of relevant quantities, but with “granules” that contain these values. We show that optimization under such granularity indeed leads to observed human behavior. In particular, for the first time, we explain the mysterious empirical dependence of betting odds on actual probabilities.This book can be recommended to all students interested in human decision-making, to researchers whose work involves human decisions, and to practitioners who design and employ systems involving human decision-making —so that they can better utilize our ability to make decisions under uncertainty.
Описание: Human Decisions Are Often Suboptimal: Phenomenon of Bounded Rationality.- Towards Explaining Other Aspects of Human Decision Making.- Towards Explaining Heuristic Techniques (Such as Fuzzy) in Expert Decision Making.- Decision Making Under Uncertainty and Restrictions on Computation Resources: From Heuristic to Optimal Techniques.- Conclusions and Future Work.
Introduction to Rational Decision Making.- Casual Function for Rational Decision Making: Application to Militarized Interstate Disputes.- Correlation Function for Rational Decision Making: Application to Epileptic Activity.- Missing Data Approaches for Rational Decision Making: Application to Anecdotal Data.- Rational Counterfactuals and Decision Making: Application to Interstate Conflict.- Flexibility-Bounded Rationality in Interstate Conflict.- Filtering Irrelevant Information for Rational Decision Making.- Group Decision Making.- Conclusion.- Appendix A: Fourier Transform, Wavelet Transform, Modal Properties and Pseudo-Modal Energies.- Appendix B: Committee of Networks.
Описание: 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.
Описание: Presents selected papers from an international workshop devoted to the theory, techniques and tools of decision analysis and support. Major trends in the development of this field are stressed, such as the tendency to place the final user of a decision support system in the centre of attention.
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