Shu-Heng Chen - Böcker

Over the past few decades, agent-based modelling and agent-based computational technologies have spread into research on business and management. Agent-based modelling takes account of individual behavior alongside interactions within and across organizations and their competitive environment, seeking to explain complex, macro-level patterns emerging from micro-level behavior. These characteristics make an agent-based approach useful for studying a number of open issues in management, including adaptive behavior and dynamics in and across organizations, variable outcomes caused by management practices, and bridging micro-and macro-levels in organizational analysis.In The Oxford Handbook of Agent-based Computational Management Science, Friederike Wall, Shu-Heng Chen, and Stephan Leitner bring together a wide array of experts in the field to give a comprehensive overview of this novel approach in management science. In particular, the volume focuses on adaptive behavior and dynamics in and across organizations, non-linearities caused by management practices, and bridging micro-and macro-levels in organizational analysis. The Handbook addresses two purposes of agent-based approaches in management science. First, the volume shows how an agent-based approach advances theory-building in management. Second, it provides an overview of agent-based technologies employed for more practical issues in management. These comprise, for example, a normative understanding of systems design, such as determining which designs provide good results.An indispensable resource on agent-based modeling in management science, this Handbook introduces its current state from theoretical and operational perspectives and discusses its future opportunities.

While the significance of networks in various human behavior and activities has a history as long as human's existence, network awareness is a recent scientific phenomenon. The neologism network science is just one or two decades old. Nevertheless, with this limited time, network thinking has substantially reshaped the recent development in economics, and almost all solutions to real-world problems involve the network element. This 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 essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The text also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. It reviews a number of pioneering and representative models in this family. Upon the given foundation, the second part reviews three primary forms of network dynamics, such as diffusions, cascades, and influences. These primary dynamics are further extended and enriched by practical networks in goods-and-service markets, labor markets, and international trade. At the end, the book considers two challenging issues using agent-based models of networks: network risks and economic growth.

The Oxford Handbook of Computational Economics and Finance provides a survey of both the foundations of and recent advances in the frontiers of analysis and action. It is both historically and interdisciplinarily rich and also tightly connected to the rise of digital society. It begins with the conventional view of computational economics, including recent algorithmic development in computing rational expectations, volatility, and general equilibrium. It then moves from traditional computing in economics and finance to recent developments in natural computing, including applications of nature-inspired intelligence, genetic programming, swarm intelligence, and fuzzy logic. Also examined are recent developments of network and agent-based computing in economics. How these approaches are applied is examined in chapters on such subjects as trading robots and automated markets. The last part deals with the epistemology of simulation in its trinity form with the integration of simulation, computation, and dynamics. Distinctive is the focus on natural computationalism and the examination of the implications of intelligent machines for the future of computational economics and finance. Not merely individual robots, but whole integrated systems are extending their "immigration" to the world of Homo sapiens, or symbiogenesis.

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.

This book aims to answer two questions that are fundamental to the study of agent-based economic models: what is agent-based computational economics and why do we need agent-based economic modelling of economy? This book provides a review of the development of agent-based computational economics (ACE) from a perspective on how artificial economic agents are designed under the influences of complex sciences, experimental economics, artificial intelligence, evolutionary biology, psychology, anthropology and neuroscience. This book begins with a historical review of ACE by tracing its origins. From a modelling viewpoint, ACE brings truly decentralized procedures into market analysis, from a single market to the whole economy. This book also reviews how experimental economics and artificial intelligence have shaped the development of ACE. For the former, the book discusses how ACE models can be used to analyse the economic consequences of cognitive capacity, personality and cultural inheritance. For the latter, the book covers the various tools used to construct artificial adaptive agents, including reinforcement learning, fuzzy decision rules, neural networks, and evolutionary computation. This book will be of interest to graduate students researching computational economics, experimental economics, behavioural economics, and research methodology.

In recent years, many thinkers have attempted to incorporate—or reintegrate—behavioural and psychological insights into traditional economic models and theoretical analyses. Under the banner of ‘behavioural economics’, they have, in particular, deconstructed the fundamental assumption that human beings and economic organizations take decisions, and make rational choices, in their own interests.This new four-volume collection from Routledge brings together foundational and the best cutting-edge research to create a unique ‘mini library’. Edited by two leading scholars in the field, it has been designed to meet the need for an authoritative reference work to make sense of the origins of the behavioural approach, and the continuing upsurge in research output.The collection is divided into six principal parts: 1. Classical Behavioural Economics; 2. Modern Behavioural Economics; 3. Behavioural Finance Theory; 4. Behavioural Game Theory; 5. Behavioural Neuroeconomics; and 6. Agent-Based Behavioural Economics and Finance. Fully indexed and with a comprehensive introduction, newly written by the editors, which places the material in its intellectual context, Behavioural Economics is an essential work of reference and is destined to be valued by scholars and students as a vital one-stop research resource.

After much development, genetic algorithms and genetic programming have become a widely accepted toolkit for computational finance. This volume is 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 modelling; 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.

This book aims to answer two questions that are fundamental to the study of agent-based economic models: what is agent-based computational economics and why do we need agent-based economic modelling of economy? This book provides a review of the development of agent-based computational economics (ACE) from a perspective on how artificial economic agents are designed under the influences of complex sciences, experimental economics, artificial intelligence, evolutionary biology, psychology, anthropology and neuroscience. This book begins with a historical review of ACE by tracing its origins. From a modelling viewpoint, ACE brings truly decentralized procedures into market analysis, from a single market to the whole economy. This book also reviews how experimental economics and artificial intelligence have shaped the development of ACE. For the former, the book discusses how ACE models can be used to analyse the economic consequences of cognitive capacity, personality and cultural inheritance. For the latter, the book covers the various tools used to construct artificial adaptive agents, including reinforcement learning, fuzzy decision rules, neural networks, and evolutionary computation. This book will be of interest to graduate students researching computational economics, experimental economics, behavioural economics, and research methodology.

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.

After a decade of development, genetic algorithms and genetic programming have become a widely accepted toolkit for computational finance.

This book is based on the International Conference on Decision Economics (DECON 2019). Highlighting the fact that important decision-making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, psychology, small and international business, management, operations, and production, the book focuses on analytics as an emerging synthesis of sophisticated methodology and large data systems used to guide economic decision-making in an increasingly complex business environment.DECON 2019 was organised by the University of Chieti-Pescara (Italy), the National Chengchi University of Taipei (Taiwan), and the University of Salamanca (Spain), and was held at the Escuela politécnica Superior de Ávila, Spain, from 26th to 28th June, 2019. Sponsored by IEEE Systems Man and Cybernetics Society, Spain Section Chapter, and IEEE Spain Section (Technical Co-Sponsor), IBM, Indra, Viewnext, Global Exchange, AEPIA-and-APPIA, with the funding supporting of the Junta de Castilla y León, Spain (ID: SA267P18-Project co-financed with FEDER funds)

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.

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 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 toproduce 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.

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?

This title brings together frontier research on complex economic systems, heterogeneous interacting agents, bounded rationality, and nonlinear dynamics in economics.

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 rationalityand 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.

After a decade's development, evolutionary computation (EC) proves to be a powerful tool kit for economic analysis. While the demand for this equipment is increasing, there is no volume exclusively written for economists. This volume for the first time helps economists to get a quick grasp on how EC may support their research. A comprehensive coverage of the subject is given, that includes the following three areas: game theory, agent-based economic modelling and financial engineering. Twenty leading scholars from each of these areas contribute a chapter to the volume. The reader will find himself treading the path of the history of this research area, from the fledgling stage to the burgeoning era. The results on games, labour markets, pollution control, institution and productivity, financial markets, trading systems design and derivative pricing, are new and interesting for different target groups. The book also includes informations on web sites, conferences, and computer software.

After a decade's development, evolutionary computation (EC) proves to be a powerful tool kit for economic analysis. While the demand for this equipment is increasing, there is no volume exclusively written for economists. This volume for the first time helps economists to get a quick grasp on how EC may support their research. A comprehensive coverage of the subject is given, that includes the following three areas: game theory, agent-based economic modelling and financial engineering. Twenty leading scholars from each of these areas contribute a chapter to the volume. The reader will find himself treading the path of the history of this research area, from the fledgling stage to the burgeoning era. The results on games, labour markets, pollution control, institution and productivity, financial markets, trading systems design and derivative pricing, are new and interesting for different target groups. The book also includes informations on web sites, conferences, and computer software.

Agent-based modeling/simulation is an emergent approach to the analysis of social and economic systems. It provides a bottom-up experimental method to be applied to social sciences such as economics, management, sociology, and politics as well as some engineering fields dealing with social activities. This book includes selected papers presented at the Sixth International Workshop on Agent-Based Approaches in Economic and Social Complex Systems held in Taipei in 2009. We have 39 presentations in the conference, and 14 papers are selected to be included in this volume. These 14 papers are then grouped into six parts: Agent-based financial markets; Financial forecasting and investment; Cognitive modeling of agents; Complexity and policy analysis; Agent-based modeling of good societies; and Miscellany. The research presented here shows the state of the art in this rapidly growing field.

Agent-based modeling/simulation is an emergent approach to the analysis of social and economic systems. It provides a bottom-up experimental method to be applied to social sciences such as economics, management, sociology, and politics as well as some engineering fields dealing with social activities. This book includes selected papers presented at the Sixth International Workshop on Agent-Based Approaches in Economic and Social Complex Systems held in Taipei in 2009. We have 39 presentations in the conference, and 14 papers are selected to be included in this volume. These 14 papers are then grouped into six parts: Agent-based financial markets; Financial forecasting and investment; Cognitive modeling of agents; Complexity and policy analysis; Agent-based modeling of good societies; and Miscellany. The research presented here shows the state of the art in this rapidly growing field.

This volume is a post-conference publication of the 4th World Congress on Social Simulation (WCSS), with contents selected from among the 80 papers originally presented at the conference. WCSS is a biennial event, jointly organized by three scientific communities in computational social science, namely, the Pacific-Asian Association for Agent-Based Approach in Social Systems Sciences (PAAA), the European Social Simulation Association (ESSA), and the Computational Social Science Society of the Americas (CSSSA). It is, therefore, currently the most prominent conference in the area of agent-based social simulation. The papers selected for this volume give a holistic view of the current development of social simulation, indicating the directions for future research and creating an important archival document and milestone in the history of computational social science. Specifically, the papers included here cover substantial progress in artificial financial markets, macroeconomic forecasting, supply chain management, bank networks, social networks, urban planning, social norms and group formation, cross-cultural studies, political party competition, voting behavior, computational demography, computational anthropology, evolution of languages, public health and epidemics, AIDS, security and terrorism, methodological and epistemological issues, empirical-based agent-based modeling, modeling of experimental social science, gaming simulation, cognitive agents, and participatory simulation. Furthermore, pioneering studies in some new research areas, such as the theoretical foundations of social simulation and categorical social science, also are included in the volume.

Agent-based simulation of the prediction market augmented with these four elements enables an examination of the effects of these elements on the prediction market from the computational aspect and hence tests the Hayek hypothesis on the basis of diverse institutional and individual characteristics.