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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.

This book highlights recent developments in the field, presented at the Social Simulation 2015 conference in Groningen, The Netherlands. It covers advances both in applications and methods of social simulation. Societal issues addressed range across complexities in economic systems, opinion dynamics and civil violence, changing mobility patterns, different land-use, transition in the energy system, food production and consumption, ecosystem management and historical processes. Methodological developments cover how to use empirical data in validating models in general, formalization of behavioral theory in agent behavior, construction of artificial populations for experimentation, replication of models, and agent-based models that can be run in a web browser.Social simulation is a rapidly evolving field. Social scientists are increasingly interested in social simulation as a tool to tackle the complex non-linear dynamics of society. Furthermore, the software and hardware tools available for social simulation are becoming more and more powerful. This book is an important source for readers interested in the newest developments in the ways in which the simulation of social interaction contributes to our understanding and managing of complex social phenomena.

The book presents the lectures delivered during a short course held at Urbino University in summer 2015 on qualitative theory of dynamical systems, included in the activities of the COST Action IS1104 “The EU in the new economic complex geography: models, tools and policy evaluation”. It provides a basic introduction to dynamical systems and optimal control both in continuous and discrete time, as well as some numerical methods and applications in economic modelling.Economic and social systems are intrinsically dynamic, characterized by interdependence, nonlinearity and complexity, and these features can only be approached using a qualitative analysis based on the study of invariant sets (equilibrium points, limit cycles and more complex attractors, together with the boundaries of their basins of attraction), which requires a trade-off between analytical, geometrical and numerical methods. Even though the early steps of the qualitative theory of dynamical systems have been incontinuous time models, in economic and social modelling discrete time is often used to describe event-driven (often decision-driven) evolving systems.The book is written for Ph.D. and master's students, post-doctoral fellows, and researchers in economics or sociology, and it only assumes a basic knowledge of calculus. However it also suggests some more advanced topics.

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.

The series is designed to bring together those mathematicians who are seriously interested in getting new challenging stimuli from economic theories with those economists who are seeking effective mathematical tools for their research. A lot of economic problems can be formulated as constrained optimizations and equilibration of their solutions. Various mathematical theories have been supplying economists with indispensable machineries for these problems arising in economic theory. Conversely, mathematicians have been stimulated by various mathematical difficulties raised by economic theories.

This book reflects the state of the art on nonlinear economic dynamics, financial market modelling and quantitative finance. It contains eighteen papers with topics ranging from disequilibrium macroeconomics, monetary dynamics, monopoly, financial market and limit order market models with boundedly rational heterogeneous agents to estimation, time series modelling and empirical analysis and from risk management of interest-rate products, futures price volatility and American option pricing with stochastic volatility to evaluation of risk and derivatives of electricity market. The book illustrates some of the most recent research tools in these areas and will be of interest to economists working in economic dynamics and financial market modelling, to mathematicians who are interested in applying complexity theory to economics and finance and to market practitioners and researchers in quantitative finance interested in limit order, futures and electricity market modelling, derivative pricing and risk management.

​The book presents a peer-reviewed collection of papers presented during the 10th issue of the Artificial Economics conference, addressing a variety of issues related to macroeconomics, industrial organization, networks, management and finance, as well as purely methodological issues. The field of artificial economics covers a broad range of methodologies relying on computer simulations in order to model and study the complexity of economic and social phenomena. The grounding principle of artificial economics is the analysis of aggregate properties of simulated systems populated by interacting adaptive agents that are equipped with heterogeneous individual behavioral rules. These macroscopic properties are neither foreseen nor intended by the artificial agents but generated collectively by them. They are emerging characteristics of such artificially simulated systems.

Dynamic Modelling and Control of National Economies 1983 contains the proceedings of the Fourth IFAC/IFORS/IIASA Conference and the 1983 SEDC Conference on Economic Dynamics and Control held at Washington D.C., USA on June17-19, 1983. Separating the 65 papers presented in the conference as chapters, this book covers a broad class of problems or notions arising both in economic theory, control applications to planning, and implementation issues. Some chapters discuss multi-level interactions of government and private sectors in economic development; inflation and economic policy in an open economy; foreign debt and exchange rate stability in a developing country; and expectations in numerical general equilibrium models. This book also explains a rational decision-making process for resource policymaking; inference of the structure of economic reasoning from natural language analysis; modeling and analysis of a national economy; and methodological issues in global modeling. Econometric analysis of the economic effects of population change, aspects of optimal estimation control strategies in econometrics, and optimal policies for interdependent economies are also discussed. This book will be useful to those engaged in economic and control theory research.

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 Seventh International Workshop on Agent-Based Approaches in Economic and Social Complex Systems held in Osaka, Japan, in 2012.At the workshop, 24 reviewed full papers were presented, and of those, 17 were selected to be included in this volume. The papers are divided into two groups as'Fundamentals of Agent-Based Modeling'and'Applications of Agent-Based Modeling'.

Advances in Stochastic Modelling and Data Analysis presents the most recent developments in the field, together with their applications, mainly in the areas of insurance, finance, forecasting and marketing. In addition, the possible interactions between data analysis, artificial intelligence, decision support systems and multicriteria analysis are examined by top researchers. Audience: A wide readership drawn from theoretical and applied mathematicians, such as operations researchers, management scientists, statisticians, computer scientists, bankers, marketing managers, forecasters, and scientific societies such as EURO and TIMS.

The Instituts Internationaux de Physique et de Chimie fondis par E. Solvay and the Institute of Nonequilibrium systems of Beijing Normal University jointly sponsored a conference on'The Complexity and Self-organization in Socio­ economic Systems'on October 17-20, 1994 at Beijing, China. The purpose of the conference was to explore the complexity and evolutionary laws of socio­ economic systems through nonlinear dynamic systems and self-organization theory. The conference was chaired by Professor M. Sanglier and Professor Fang Fukang and was introduced by the Nobel prize winner, Professor I. Prigogine and the vice director of the Chinese National System Reform Committee, Mr. Wu Jie. The conference was held at an important time. On the one hand, the research in the natural sciences about the evolution of complex systems has made great progress, modern scientific theories such as nonlinear dynamic system theory and self-organization theory are becoming more and more mature and a series of methods dealing with these complex systems are being developed which enable us to understand and study non equilibrium, uncertainty and instability. On the other hand, human societies around the world witness a general increase of connectedness, interactivity and an increase of reaction speeds to decisions. In this context, the deterministic, linear way of thinking becomes more and more inadequate and this stimulates the development of non linear science.

This volume records the proceedings of the 22nd Annual International Con­ ference of the International Simulation and Gaming Association (ISAGA), 15-19 July, 1991, Kyoto, Japan, sponsored by the Science Council of Japan and the Japanese Association of Simulation and Gaming (JASAG). The con­ ference theme was Global Modeling for Solving Global Problems. The first 2 days of the conference were held in the magnificent Kyoto International Conference Hall; the 3rd day was spent admiring the floats of the famous Gion Festival in the exquisite city of Kyoto and the Daibutsu (or Great Buddha) of the Todaiji Temple in Nara and visiting one of the Sharp factories. During the last 2 days of the conference we were made most welcome in the Faculty of International Relations of Ritsumeikan University. The day after the conference, a number of delegates went to Hiroshima (the Peace Memorial Hall, Museum and Park) and also to one of Japan's'Scenic Trio,'the island of Miyajima with its breathtaking views and the Itsukushima Shrine. The conference was attended by some 400 delegates from over 30 different countries. Over 100 sessions, both theoretical and practical, were given: keynote speeches, round-table discussions, workshops, papers. This volume reflects most of those sessions, in the form of either a full paper or a short abstract.

Researchers in the natural sciences are faced with problems that require a novel approach to improve the quality of forecasts of processes that are sensitive to environmental conditions. Nonlinearity of a system may significantly complicate the predictability of future states: a small variation of parameters can dramatically change the dynamics, while sensitive dependence of the initial state may severely limit the predictability horizon. Uncertainties also play a role. This volume addresses such problems by using tools from chaos theory and systems theory, adapted for the analysis of problems in the environmental sciences. Sensitive dependence on the initial state (chaos) and the parameters are analyzed using methods such as Lyapunov exponents and Monte Carlo simulation. Uncertainty in the structure and the values of parameters of a model is studied in relation to processes that depend on the environmental conditions. These methods also apply to biology and economics. For research workers at universities and (semi)governmental institutes for the environment, agriculture, ecology, meteorology and water management, and theoretical economists.

Proceedings of a Franco-Dutch Conference held at Tilburg University, April 1979

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 book contains a selection of the best theoretical and applied papers from the inaugural International Choice Modelling Conference. The conference was organised by the Institute for Transport Studies at the University of Leeds and held in Harrogate, North Yorkshire on 30 March to 1 April 2009. The conference brought together leading researchers and practitioners from across the many different areas in which choice modelling is a key technique for understanding behaviour and evaluating policy. The diversity of the field was reflected in presentations by both academics and practitioners, coming from six continents and a variety of fields including transport and economics. Key contributions include papers from Professor Daniel McFadden, from the University of California, Berkeley - Nobel Prize laureate in Economics and chief architect of random utility modelling. The conference also included keynote presentations by five other leading choice modellers, namely Professor Moshe Ben-Akiva, Professor Chandra Bhat, Professor Michel Bierlaire, Professor David Hensher, and Professor Riccardo Scarpa.

Simulation is used in economics to solve large econometric models, for large-scale micro simulations, and to obtain numerical solutions for policy design in top-down established models. But these applications fail to take advantage of the methods offered by artificial economics (AE) through artificial intelligence and distributed computing. AE is a bottom-up and generative approach of agent-based modelling developed to get a deeper insight into the complexity of economics. AE can be viewed as a very elegant and general class of modelling techniques that generalize numerical economics, mathematical programming and micro simulation approaches. The papers presented in this book address methodological questions and applications of AE to macroeconomics, industrial organization, information and learning, market dynamics, finance and financial markets.

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 (ABM/ABS) is an emerging field that enables bottom-up and experimental analysis in social sciences such as economics, management, sociology and politics. The chapters of this book are the selected papers from those presented the Third International Workshop on Agent-Based Approaches in Economic and Social Complex Systems held in Tokyo, Japan in 2005. Articles in this book covers methodological issues, computational model/software, combination with gaming simulation, and real-world applications to economic, management/organizational and social issues.

In August 2005, a small but important conference took place at Chuo University in Tokyo, Japan. The Chuo Meeting on Economics of Time and Space 2005 (Chuo METS 05) aimed to enrich the respective disciplines of the economics of time (dynamic economics) and the economics of space (spatial economics) and to expand their applicability in the real world. The chapters contained herein are based on the papers presented at that conference.

Perceiving the economy as a complex dynamic system, generates a need for new tools for its study. As a constructive simulation method, Agent-Based Computational Economics (ACE) has in recent years proven its strength and extensive applicability. Fields of study are widely spread within economics, with a cluster around financial markets. This book is based on communications given at AE'2006 (Aalborg, Denmark) – the second symposium on Artificial Economics, and covers both wellknown questions of economics, like the existence of market efficiency, as well as new questions raised by the new tools, for example questions related to networks of social interaction.

This book contains a collection of original and state-of-the-art contributions in rational choice and general equilibrium theory. Among the topics are preferences, demand, equilibrium, core allocations, and testable restrictions. The contributing authors are Daniel McFadden, Rosa Matzkin, Emma Moreno-Garcia, Roger Lagunoff, Yakar Kannai, Myrna Wooders, James Moore, Ted Bergstrom, Luca Anderlini, Lin Zhou, Mark Bagnoli, Alexander Kovalenkov, Carlos Herves-Beloso, Michaela Topuzu, Bernard Cornet, Andreu Mas-Colell and Nicholas Yannelis.

Understanding the mechanism of a socio-economic system requires more than an understanding of the individuals that comprise the system. It also requires understanding how individuals interact with each other, and how the agg- gated outcome can be more than the sum of individual behaviors. This book contains the papers fostering the formation of an active multi-disciplinary community on socio-economic systems with the exciting new?elds of age- based modeling and econophysics. We especially intend to increase the awareness of researchers in many?elds with sharing the common view many economic and social activities as collectives of a large-scale heterogeneous and interacting agents. Economists seek to understand not only how individuals behave but also how the interaction of many individuals leads to complex outcomes. Age- based modeling is a method for studying socio-economic systems exhibiting the following two properties: (1) the system is composed of interacting agents, and (2) the system exhibits emergent properties, that is, properties arising from the interactions of the agents that cannot be deduced simply by agg- gating the properties of the system's components. When the interaction of the agents is contingent on past experience, and especially when the agents continually adapt to that experience, mathematical analysis is typically very limited in its ability to derive the outcome.

Agent-based Computational Economics (ACE) is a new discipline of economics, largely grounded on concepts like evolution, auto-organisation and emergence: it intensively uses computer simulations as well as artificial intelligence, mostly based on multi-agents systems. The purpose of this book is to give an up-to date view of the scientific production in the fields of Agent-based Computational Economics (mainly in Market Finance and Game Theory). Based on communications given at AE'2005 (Lille, USTL, France), this book offers a wide panorama of recent advances in ACE (both theoretical and methodological) that will interest academics as well as practitioners.

Economic application of nonlinear dynamics, microscopic agent-based modelling, and the use of artificial intelligence techniques as learning devices of boundedly rational actors are among the most exciting interdisciplinary ventures of economic theory over the past decade. This volume provides us with a most fascinating series of examples on'complexity in action'exemplifying the scope and explanatory power of these innovative approaches.

This volume contains papers presented at the IFAC symposium on Modeling and control of Economic Systems (SME 2001), which was held at the university of Klagenfurt, Austria. The symposium brought together scientists and users to explore current theoretical developments of modeling techniques for economic systems. It contains a section of plenary, invited and contributed papers presented at the SME 2001 symposium. The papers presented in this volume reflect advances both in methodology and in applications in the area of modeling and control of economic systems.

Adaptive Economic Models provides information pertinent to the adaptive processes in economics. This book discusses the developments on research in the field of adaptive economics. Organized into 23 chapters, this book begins with an overview of the study of economic processes using concepts of adaptation. This text then explains how concepts arising from biology can be formulated in such a way that they can be a source of insight into man's social systems. Other chapters present a general view of the adaptation of the firm to its environment and discuss how a firm with a definite commodity in mind can decide whether to enter a given established market. This book discusses as well the simple duopoly problem in which firms are in error in the sense that they specify an incomplete model and add a random error term. The final chapter deals with the set of models and problems for the development of a theory of money and financial institutions. This book is a valuable resource for economic theorists and economists.

For the mathematical modeling of complex system behavior, dynamical systems play an increasing role. The flexibility and very rich phenomenology exhibited by such systems make them indispensible in this context. Control theory for dynamical systems is also a highly active field of research where a number of important results have been achieved recently.This combined course and workshop deals with recent results regarding dynamical systems and control theory, primarily in differential geometric terms as well as the applications of these fields to biological systems, with an emphasis on various aspects of the immune system and on neural networks.