The chapters of this book are the selected papers from those presented at the Third International Workshop on Agent-Based Approaches in Economic and Social Complex Systems held in Tokyo, Japan in 2005. Articles cover methodological issues, computational model/software, combination with gaming simulation, and real-world applications to economic, management/organizational and social issues.

This volume explores the field of artificial intelligence and features in-depth coverage of important theoretical areas including computational organization, computational economics, computational approaches in social science, and game theory. The conception of the multi-agent system is particularly attractive, as it promises autonomy based on the conceptual speciality of a rational agent as well as collective behaviour through interactions.

This book includes many cases that provide new perspectives in developing agent-based modeling and simulation. The real problems are complex, and sophisticated methodology is needed to handle them. Agent-based modeling and simulation is one methodology that provides a bottom-up experimental approach applicable to social sciences such as economics, management, sociology, and politics as well as some engineering fields dealing with social activities. However, to improve the applicability of agent-based modeling and simulation methods, a new perspective is needed. In this book, that new perspective is developed and utilized to deal with many cases of real-world problems such as the supply chain, land use and land cover, transportation, health, services, economics, and social problems. The cases are selected from papers presented at the Ninth International Workshop on Agent-Based Approaches in Economic and Social Complex Systems held in Bali, Indonesia, in 2015. At the workshop, 29 reviewed full papers were presented, and of those, 16 were selected to be included in this volume.

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 Fifth International Workshop on Agent-Based Approaches in Economic and Social Complex Systems held in Tokyo in 2007. It contains two invited papers given as the plenary and invited talks in the workshop and 21 papers presented in the six regular sessions: Organization and Management; Fundamentals of Agent-Based and Evolutionary Approaches; Production, Services and Urban Systems; Agent-Based Approaches to Social Systems; and Market and Economics I and II. 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.

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 Eighth International Workshop on Agent-Based Approaches in Economic and Social Complex Systems held in Tokyo, Japan, in 2013. At the workshop, 23 reviewed full papers were presented and of those, 13 were selected to be included in this volume.

This volume examines all aspects of using agent or individual-based simulation. This approach represents systems as individual elements having their own set of differing states and internal processes. The interactions between elements in the simulation represent interactions in the target systems. What makes this "social" is that it can represent an observed society. Social systems include all those systems where the components have individual agency but also interact with each other. This includes human societies and groups, but also increasingly socio-technical systems where the internet-based devices form the substrate for interaction. These systems are central to our lives, but are among the most complex known. This poses particular problems for those who wish to understand them. The complexity often makes analytic approaches infeasible but, on the other hand, natural language approaches are also inadequate for relating intricate cause and effect. This is why individual and agent-based computational approaches hold out the possibility of new and deeper understanding of such systems. This handbook marks the maturation of this new field. It brings together summaries of the best thinking and practices in this area from leading researchers in the field and constitutes a reference point for standards against which future methodological advances can be judged. This second edition adds new chapters on different modelling purposes and applying software engineering methods to simulation development. Revised existing content will keep the book up-to-date with recent developments. This volume will help those new to the field avoid "reinventing the wheel" each time, and give them a solid and wide grounding in the essential issues. It will also help those already in the field by providing accessible overviews of current thought. The material is divided into four sections: Introduction, Methodology, Mechanisms, and Applications. Each chapter starts with a very brief section called ‘Why read this chapter?’ followed by an abstract, which summarizes the content of the chapter. Each chapter also ends with a section on ‘Further Reading’. Whilst sometimes covering technical aspects, this second edition of Simulating Social Complexity is designed to be accessible to a wide range of researchers, including both those from the social sciences as well as those with a more formal background. It will be of use as a standard reference text in the field and also be suitable for graduate level courses.

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.

This reader-friendly textbook is the first work of its kind to provide a unified Introduction to Computational Social Science (CSS). Four distinct methodological approaches are examined in detail, namely automated social information extraction, social network analysis, social complexity theory and social simulation modeling. The coverage of these approaches is supported by a discussion of the historical context, as well as by a list of texts for further reading. Features: highlights the main theories of the CSS paradigm as causal explanatory frameworks that shed new light on the nature of human and social dynamics; explains how to distinguish and analyze the different levels of analysis of social complexity using computational approaches; discusses a number of methodological tools; presents the main classes of entities, objects and relations common to the computational analysis of social complexity; examines the interdisciplinary integration of knowledge in the context of social phenomena.

This volume analyses, from a computational point of view, how culture may arise, develop and evolve through time. The four sections in this book examine and analyse the modelling of culture, group and organisation culture, culture simulation, and culture-sensitive technology design. Different research disciplines have different perspectives on culture, making it difficult to compare and integrate different concepts and models of culture. By taking a computational perspective this book nevertheless enables the integration of concepts that play a role in culture, even though they might originate from different disciplines. Culture is usually regarded as something vague and qualitative and thus difficult to deal with in a computational and formal setting. Taking a computational approach to culture thus encompasses a twofold risk: taking a too simplistic approach to cultural influence on behaviour; or trying to capture too much, hence not leading to useful computational tools. However, the approaches and insights in this collection show how different perspectives by leading researchers described in thirteen chapters still can form a coherent picture. The book thus illustrates the potential of using computing systems to better understand culture. By describing methods, theories and concrete application results about the integration of cultural aspects into computer systems, this book provides inspiration to researchers of all disciplines alike and presents the start of an interdisciplinary dialogue on culture.