Shu-Heng Chen

L. C. Jain

Chung-Ching Tai

"This book identifies the economic as well as financial problems that may be solved efficiently with computational methods and explains why those problems should best be solved with computational methods"--Provided by publisher.

A Perspective from Computational Intelligence

Computational Economics

Ngoc Thanh Nguyen

Yasushi Kambayashi

Petre Dini

Munehiro Takimoto

This book, AICON 2022, constitutes the post-conference proceedings of the 4th EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2022, held in Hiroshima, Japan, in November 30- December 1, 2022. The 9 full papers and 4 short papers were carefully reviewed and selected from 36 submissions. The papers detail research in the areas of AI and communication systems related to intelligent systems and computational intelligence for communication and networks. They are organized in topical sections on AI and networks; machine learning; and evolutionary computation.

4th EAI International Conference, AICON 2022, Hiroshima, Japan, November 30 - December 1, 2022, Proceedings

Artificial Intelligence for Communications and Networks

Edgardo Bucciarelli

Juan M. Corchado

The special session on Decision Economics (DECON) is a scientific forum held annually and intended to share ideas, projects, research results, models and experiences associated with the complexity of behavioural decision processes and socio‐economic phenomena. DECON 2017 was held at the Polytechnic of Porto, ISEP, Portugal, as part of the 14th International Conference on Distributed Computing and Artificial Intelligence. For the second consecutive year, the Editors of this book have drawn inspiration from Herbert A. Simon’s immense body of work and argue that Simon precipitated something akin to a revolution in microeconomics focused on the concept of decision‐making. Further, it is worth noting that the recognition of relevant decision‐making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, small and international business management, operations, and production. Therefore, decision‐making issues are of fundamental importance in all branches of economics addressed both deductively and inductively. Not surprisingly, the study of decision‐making has seen growing empirical research efforts in the economic literature over the last sixty years and, more recently, a variety of insightful cutting‐edge experimental, behavioural and computational approaches. Additionally, the awareness regarding generalizations and reductions to express economic concepts has led, on the one hand, to an increasing risk of spreading the language of mathematics as a rhetorical tool and, on the other hand, to an oversimplification and overlooking of some crucial details, especially when it comes to human decisions and, hence, economic behaviour. That awareness, however, has helped to produce an extraordinary volume of empirical research aimed at discovering how economic agents cope with complex decisions. In this sense, the international scientific community acknowledges Herbert A. Simon’s research endeavours to understand the processes involved in economic decision‐making and their implications for the advancement of economic professions. Within the field of decision‐making, indeed, Simon’s rejection of the standard decision‐making models used in neoclassical economics inspired social scientists worldwide to develop research programmes in order to study decision‐making empirically. The main achievements concern decision‐making for individuals, firms, markets, governments, institutions, and, last but not least, science and research.

Distributed Computing and Artificial Intelligence, 14th International Conference

Decision Economics: In the Tradition of Herbert A. Simon's Heritage

This edited volume focuses on big data implications for computational social science and humanities from management to usage. The first part of the book covers geographic data, text corpus data, and social media data, and exemplifies their concrete applications in a wide range of fields including anthropology, economics, finance, geography, history, linguistics, political science, psychology, public health, and mass communications. The second part of the book provides a panoramic view of the development of big data in the fields of computational social sciences and humanities. The following questions are addressed: why is there a need for novel data governance for this new type of data?, why is big data important for social scientists?, and how will it revolutionize the way social scientists conduct research? With the advent of the information age and technologies such as Web 2.0, ubiquitous computing, wearable devices, and the Internet of Things, digital society has fundamentally changed what we now know as "data", the very use of this data, and what we now call "knowledge". Big data has become the standard in social sciences, and has made these sciences more computational. Big Data in Computational Social Science and Humanities will appeal to graduate students and researchers working in the many subfields of the social sciences and humanities.

Big Data in Computational Social Science and Humanities

Juan Manuel Corchado

The special session on Decision Economics (DECON) is a scientific forum held annually, which is focused on sharing ideas, projects, research results, models, and experiences associated with the complexity of behavioural decision processes and socio‐economic phenomena. In 2018, DECON was held at Campus Tecnológico de la Fábrica de Armas, University of Castilla-La Mancha, Toledo, Spain, as part of the 15th International Conference on Distributed Computing and Artificial Intelligence. For the third consecutive year, this book have drawn inspiration from Herbert A. Simon’s interdisciplinary legacy and, in particular, is devoted to designs, models, and techniques for boundedly rational decisions, involving several fields of study and expertise. It is worth noting that the recognition of relevant decision‐making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, small and international business management, operations, and production. Therefore, decision‐making issues are of fundamental importance in all branches of economics addressed with different methodological approaches. As a matter of fact, the study of decision‐making has become the focus of intense research efforts, both theoretical and applied, forming a veritable bridge between theory and practice as well as science and business organisations, whose pillars are based on insightful cutting‐edge experimental, behavioural, and computational approaches on the one hand, and celebrating the value of science as well as the close relationship between economics and complexity on the other. In this respect, the international scientific community acknowledges Herbert A. Simon’s research endeavours to understand the processes involved in economic decision‐making and their implications for the advancement of economic professions. Within the field of decision‐making, indeed, Simon has become a mainstay of bounded rationality and satisficing. His rejection of the standard (unrealistic) decision‐making models adopted by neoclassical economists inspired social scientists worldwide with the purpose to develop research programmes aimed at studying decision‐making empirically, experimentally, and computationally. The main achievements concern decision‐making for individuals, firms, markets, governments, institutions, and, last but not least, science and research. This book of selected papers tackles these issues that Simon broached in a professional career spanning more than sixty years. The Editors of this book dedicated it to Herb.

Decision Economics. Designs, Models, and Techniques for Boundedly Rational Decisions

Ying-Fang Kao

Ragupathy Venkatachalam

Ye-Rong Du

This title brings together frontier research on complex economic systems, heterogeneous interacting agents, bounded rationality, and nonlinear dynamics in economics. The book contains the proceedings of the CEF2015 (21st Computing in Economics in Finance), held 20-22 June 2015 in Taipei, Taiwan, and addresses some of the important driving forces for various emergent properties in economies, when viewed as complex systems. The breakthroughs reported in this book are a result of an interdisciplinary approach and simulation remains the unifying theme for these papers as they deal with a wide range of topics in economics. The text is a valuable addition to the efforts in promoting the complex systems view in economic science. The computational experiments reported in the book are both transparent and replicable. Complex System Modeling and Simulation in Economics and Finance is useful for graduate courses of complex systems, with particular focus on economics and finance. At the same time it serves as a good overview for researchers who are interested in the topic.

Complex Systems Modeling and Simulation in Economics and Finance

Shabnam Mousavi

Floris Heukelom

Kurt Dopfer

Roger Frantz

There is no doubt that behavioral economics is becoming a dominant lens through which we think about economics. Behavioral economics is not a single school of thought but representative of a range of approaches, and uniquely, this volume presents an overview of them. The wide spectrum of international contributors each provides an exploration of a central approach, aspect or topic in behavorial economics. Taken together, the whole volume provides a comprehensive overview of the subject which considers both key developments and future possibilities. Part One presents several different approaches to behavioural economics, including George Katona, Ken Boulding, Harvey Leibenstein, Vernon Smith, Herbert Simon, Gerd Gigerenzer, Daniel Kahneman, and Richard Thaler. This section looks at the origins and development of behavioral economics and compares and contrasts the work of these scholars who have been so influential in making this area so prominent. Part Two presents applications of behavioural economics including nudging; heuristics; emotions and morality; behavioural political economy, education, and economic innovation. The Routledge Handbook of Behavioral Economics is ideal for advanced economics students and faculty who are looking for a complete state-of-the-art overview of this dynamic field.

Routledge Handbook of Behavioral Economics

After a decade of development, genetic algorithms and genetic programming have become a widely accepted toolkit for computational finance. Genetic Algorithms and Genetic Programming in Computational Finance is a pioneering volume devoted entirely to a systematic and comprehensive review of this subject. Chapters cover various areas of computational finance, including financial forecasting, trading strategies development, cash flow management, option pricing, portfolio management, volatility modeling, arbitraging, and agent-based simulations of artificial stock markets. Two tutorial chapters are also included to help readers quickly grasp the essence of these tools. Finally, a menu-driven software program, Simple GP, accompanies the volume, which will enable readers without a strong programming background to gain hands-on experience in dealing with much of the technical material introduced in this work.

Genetic Algorithms and Genetic Programming in Computational Finance

Accompanying CD-ROM contains ... "a menu-driven software program, Simple GP ..." p, [4] of cover.

Akira Namatame

The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The authors begin with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling's segregation model and Axelrod's spatial game. The text shows that the modern network science mainly driven by game-theorists andsociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks.

Shu-Heng Chen

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