Overview
- Provides a timely consideration of major concepts by which Decision Economics is understood as an emerging, novel discipline, such as the study of agents' behaviour and their interactions under uncertainty, in order to discuss, inter alia, whether standard economics can be considered a science or even an academic pursuit.
- Illustrates the potential, importance, and breadth of algorithmic social science research in this novel discipline, bringing together cognitive sciences, economics, and mathematics to analyse the decision-making, both normatively and positively, and the related market functioning within the ecosystem.
- Includes contributions by renowned scientists, scholars, and leaders of research, offering new ideas that help launch into the economic theory, methodology, and analysis in the 21st Century.
Part of the book series: Studies in Computational Intelligence (SCI, volume 990)
Included in the following conference series:
Conference proceedings info: DECON 2020.
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Table of contents (25 papers)
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Front Matter
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Part I: Turing Test: Computable Humanities
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Front Matter
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Part II: Minds: Cognitive, Behavioural, and Experimental Perspectives
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Front Matter
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Part III: Machine Learning: Application and Analysis
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Front Matter
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Other volumes
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Decision Economics: Minds, Machines, and their Society
Keywords
About this book
This book is the result of a multi-year research project led and sponsored by the University of Chieti-Pescara, National Chengchi University, University of Salamanca, and Osaka University. It is the fifth volume to emerge from that international project, held under the aegis of the United Nations Academic Impact in 2020. All the essays in this volume were (virtually) discussed at the University of L’Aquila―as the venue of the 2nd International Conference on Decision Economics, a three-day global gathering of approximately one hundred scholars and practitioners—and were subjected to thorough peer review by leading experts in the field. The essays reflect the extent, diversity, and richness of several research areas, both normative and descriptive, and are an invaluable resource for graduate-level and PhD students, academics, researchers, policymakers and other professionals, especially in the social and cognitive sciences.
Given its interdisciplinary scope, the book subsequently delivers new approaches on how to contribute to the future of economics, providing alternative explanations for various socio-economic issues such as computable humanities; cognitive, behavioural, and experimental perspectives in economics; data analysis and machine learning as well as research areas at the intersection of computer science, artificial intelligence, mathematics, and statistics; agent-based modelling and the related. The editors are grateful to the scientific committee for its continuous support throughout the research project as well as to the many participants for their insightful comments and always probing questions. In any case, the collaboration involved in the project extends far beyond the group of authors published in this volume and is reflected in the quality of the essays published over the years.
Editors and Affiliations
Bibliographic Information
Book Title: Decision Economics: Minds, Machines, and their Society
Editors: Edgardo Bucciarelli, Shu-Heng Chen, Juan M. Corchado, Javier Parra D.
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-75583-6
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-75582-9Published: 17 August 2021
eBook ISBN: 978-3-030-75583-6Published: 16 August 2021
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XXIV, 272
Number of Illustrations: 17 b/w illustrations, 61 illustrations in colour
Topics: Computational Intelligence, Machine Learning, Economic Theory/Quantitative Economics/Mathematical Methods