There has been an increase in attention toward systems involving large numbers of small players, giving rise to the theory of mean field games, mean field type control and nonlinear Markov games. Exhibiting various real world problems involving major and minor agents, this book presents a systematic continuous-space approximation approach for mean-field interacting agents models and mean-field games models. After describing Markov-chain methodology and a modeling of mean-field interacting systems, the text presents various structural conditions on the chain to yield respective socio-economic models, focusing on migration models via binary interactions. The specific applications are wide-ranging – including inspection and corruption, cyber-security, counterterrorism, coalition building and network growth, minority games, and investment policies and optimal allocation – making this book relevant to a wide audience of applied mathematicians interested in operations research, computer science, national security, economics, and finance.

There has been an increase in attention toward systems involving large numbers of small players, giving rise to the theory of mean field games, mean field type control and nonlinear Markov games. Exhibiting various real world problems involving major and minor agents, this book presents a systematic continuous-space approximation approach for mean-field interacting agents models and mean-field games models. After describing Markov-chain methodology and a modeling of mean-field interacting systems, the text presents various structural conditions on the chain to yield respective socio-economic models, focusing on migration models via binary interactions. The specific applications are wide-ranging - including inspection and corruption, cyber-security, counterterrorism, coalition building and network growth, minority games, and investment policies and optimal allocation - making this book relevant to a wide audience of applied mathematicians interested in operations research, computer science, national security, economics, and finance.

Actor-systems dynamics is an innovative, multidisciplinary methodology for investigating and analyzing social struggles over economic resources and the related interplay between economic and socio-political institutions and processes. The authors, sociologists and economists, offer a systemic perspective on contemporary socio-economic issues such as economic crisis, unemployment, inflation, economic democracy and development; in their analyses, they identify several of the key factors that drive people to interact, to initiate change and transformation as well as to resist such change. Major underlying themes in the book are: Conflict over the distribution of economic resources and economic policies and institutions; the structural bases of economic inequality and conflict; the shaping and reshaping of socio-economic institutions, and the contradictions, conflicts and instabilities evoked by such developments; the failure of orthodox economic theories, including Keynesianism, in the face of recurrent economic crises and instabilities; the development and application of an open, dynamic actor-oriented systems theory – grounded in the social sciences – addressing complex socio-economic phenomena in ways diverging substantially from conventional economics. All in all, the papers collected here deal, on the one hand, with social power, conflict, and struggle concerning economic resources and institutions and, on the other hand, the structural and other factors which drive powering initiatives, conflict, and social innovation and transformation. The book is addressed to a broad spectrum of social and managerial scientists concerned with socio-economic issues, institutions, and development.

First Published in 1986. Routledge is an imprint of Taylor & Francis, an informa company.

In agent-based modeling the focus is very much on agent-based simulation, as simulation is a very important tool for agent-based modeling. We also use agent-based simulation in this book with a stress on the mathematical foundation of agent-based modeling. We introduce two original mathematical frameworks, a theory of SLD (Social Learning Dynamics) and an axiomatic theory of economic exchange (Exchange Algebra) among agents. Exchange algebra gives bottom-up reconstruction of SNA (System of National Accountings). SLD provides the concept of indirect control of socio-economic systems to manage structural change and its stability. We also compare agent-based simulation with gaming simulation and investigate the epistemological foundation of agent-based modeling.

Mainstream economics generally assumes a universalistic market-oriented economic behavior that drives countries to adopt one economic system, with marginal variations. This book extends the scope of theory and applications by asserting that other distinct behaviors evolve and dominate in other economic systems. Systemic differences arise from distinct social, political and economic behavioral-motivational types that associate with intensive agent activity in household, state and firm settings. External conditions, historical events, and agent interactions ultimately result in domination of one motivational type over others; thus determining distinct profiles of structure, conduct, and performance in different economic systems, that are generally observed in the adopting countries.The book validates the theory empirically, traces the historical evolution of the respective economic systems in the world regions and evaluates their responses to various systemic failures such as monopoly, uncertainties, externalities and collective needs. The evaluation is extended to structural changes and system performance regarding growth and distribution.This book draws on microeconomics, welfare economics, development economics and the international economy. The book projects the influence potential of leading countries/systems, and treats effects of displacement of incumbent leaders (US, Japan) by newcomer leaders (China, India) on system competition and on world governance.

Recent applications of evolutionary game theory in the merging fields of the mathematical and social sciences are brilliantly portrayed in this book, which highlights social physics and shows how the approach can help to quantitatively model complex human–environmental–social systems. First, readers are introduced to the fundamentals of evolutionary game theory. The two-player, two-strategy game, or the 2 × 2 game, is presented as an archetype to help understand the difficulty of cooperating for survival against defection in common social contexts. Subsequently, the book explains the theoretical background of the multi-player, two-strategy game, which may be more widely applicable than the 2 × 2 game for social dilemmas. The latest applications of 2 × 2 games are also discussed to explore how integrated reciprocity mechanisms can solve social dilemmas. In turn, the book describes two practical areas in which evolutionary game theory has been applied. The first concerns traffic flow analysis. In conventional interpretations, traffic flow can be understood by means of fluid dynamics, in which the flow of vehicles is evaluated as a continuum body. Such a simple idea, however, does not work well in reality, particularly if a driver’s decision-making process is considered. Various dilemmas involve complex structures that depend primarily on traffic density, a revelation that should help establish a practical solution for reducing traffic congestion. Second, the book provides keen insights into how powerful evolutionary game theory can be in the context of epidemiology. Both approaches, quasi-analytical and multi-agent simulation, can clarify how an infectious disease such as seasonal influenza spreads across a complex social network, which is significantly affected by the public attitude toward vaccination. A methodology is proposed for the optimum design of a public vaccination policy incorporating subsidies to efficiently increase vaccination coverage while minimizing the social cost.

This volume collects papers based on plenary and invited talks given at the 50th Barrett Memorial Lectures on Approximation, Applications, and Analysis of Nonlocal, Nonlinear Models that was organized by the University of Tennessee, Knoxville and held virtually in May 2021. The three-day meeting brought together experts from the computational, scientific, engineering, and mathematical communities who work with nonlocal models. These proceedings collect contributions and give a survey of the state of the art in computational practices, mathematical analysis, applications of nonlocal models, and explorations of new application domains. The volume benefits from the mixture of contributions by computational scientists, mathematicians, and application specialists. The content is suitable for graduate students as well as specialists working with nonlocal models and covers topics on fractional PDEs, regularity theory for kinetic equations, approximation theory for fractional diffusion, analysis of nonlocal diffusion model as a bridge between local and fractional PDEs, and more.

What are the principles that keep our society together? This question is even more difficult to answer than the long-standing question, what are the forces that keep our world together. However, the social challenges of humanity in the 21st century ranging from the financial crises to the impacts of globalization, require us to make fast progress in our understanding of how society works, and how our future can be managed in a resilient and sustainable way. This book can present only a few very first steps towards this ambitious goal. However, based on simple models of social interactions, one can already gain some surprising insights into the social, ``macro-level'' outcomes and dynamics that is implied by individual, ``micro-level'' interactions. Depending on the nature of these interactions, they may imply the spontaneous formation of social conventions or the birth of social cooperation, but also their sudden breakdown. This can end in deadly crowd disasters or tragedies of the commons (such as financial crises or environmental destruction). Furthermore, we demonstrate that classical modeling approaches (such as representative agent models) do not provide a sufficient understanding of the self-organization in social systems resulting from individual interactions. The consideration of randomness, spatial or network interdependencies, and nonlinear feedback effects turns out to be crucial to get fundamental insights into how social patterns and dynamics emerge. Given the explanation of sometimes counter-intuitive phenomena resulting from these features and their combination, our evolutionary modeling approach appears to be powerful and insightful. The chapters of this book range from a discussion of the modeling strategy for socio-economic systems over experimental issues up the right way of doing agent-based modeling. We furthermore discuss applications ranging from pedestrian and crowd dynamics over opinion formation, coordination, and cooperation up to conflict, and also address the response to information, issues of systemic risks in society and economics, and new approaches to manage complexity in socio-economic systems. Selected parts of this book had been previously published in peer reviewed journals.

Information and communication technology, in particular artificial intelligence, can be used to support economy and commerce using digital means. This book is about agents and multi-agent distributed systems applied to digital economy and e-commerce to meet, improve, and overcome challenges in the digital economy and e-commerce sphere. Agent and multi-agent solutions are applied in implementing real-life, exciting developments associated with the need to eliminate problems of distributed systems. The book presents solutions for both technology and applications, illustrating the possible uses of agents in the enterprise domain, covering design and analytic methods, needed to provide a solid foundation required for practical systems. More specifically, the book provides solutions for the digital economy, e-sourcing clusters in network economy, and knowledge exchange between agents applicable to online trading agents, and security solutions to both digital economy and e-commerce. Furthermore, it offers solutions for e-commerce, such as, mapping and alignment of ontologies for business, negotiation, automated auctions, recommender systems to support traders in business activities, and game simulations.