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 book presents the fundamentals of evolutionary game theory and applies them to the analysis of epidemics, which is of paramount importance in the aftermath of the worldwide COVID-19 pandemic. The primary objective of this monograph is to deliver a powerful tool to model and analyze the spread of an infectious disease during a pandemic as well as the human decision dynamics. The book employs a variant of the "vaccination game," in which a mathematical epidemiological model dovetails with evolutionary game theory. From a social physics standpoint, this book introduces an extended concept of the vaccination game starting from the fundamental issues and touching on the newest practical applications. The book first outlines the fundamental basis of evolutionary game theory, in which a two-player and two-strategy game, the so-called 2 × 2 game, and a multi-player game are concisely introduced, and the important issue of how social dilemmas are quantified is highlighted. Subsequently, the book discusses various recent applications of the extended concept of the vaccination game so as to quantitatively evaluate provisions other than vaccination, including practical intermediate protective measures such as mask-wearing, efficiency of quarantine compared with that of isolation policies for suppressing epidemics, efficiency of preemptive versus late vaccination, and optimal subsidy policies for vaccination.

This book presents the fundamentals of evolutionary game theory and applies them to the analysis of epidemics, which is of paramount importance in the aftermath of the worldwide COVID-19 pandemic. The primary objective of this monograph is to deliver a powerful tool to model and analyze the spread of an infectious disease during a pandemic as well as the human decision dynamics. The book employs a variant of the “vaccination game,” in which a mathematical epidemiological model dovetails with evolutionary game theory. From a social physics standpoint, this book introduces an extended concept of the vaccination game starting from the fundamental issues and touching on the newest practical applications. The book first outlines the fundamental basis of evolutionary game theory, in which a two-player and two-strategy game, the so-called 2 × 2 game, and a multi-player game are concisely introduced, and the important issue of how social dilemmas are quantified is highlighted. Subsequently, the book discusses various recent applications of the extended concept of the vaccination game so as to quantitatively evaluate provisions other than vaccination, including practical intermediate protective measures such as mask-wearing, efficiency of quarantine compared with that of isolation policies for suppressing epidemics, efficiency of preemptive versus late vaccination, and optimal subsidy policies for vaccination.

This book presents an introduction to Evolutionary Game Theory (EGT) which is an emerging field in the area of complex systems attracting the attention of researchers from disparate scientific communities. EGT allows one to represent and study several complex phenomena, such as the emergence of cooperation in social systems, the role of conformity in shaping the equilibrium of a population, and the dynamics in biological and ecological systems.Since EGT models belong to the area of complex systems, statistical physics constitutes a fundamental ingredient for investigating their behavior. At the same time, the complexity of some EGT models, such as those realized by means of agent-based methods, often require the implementation of numerical simulations. Therefore, beyond providing an introduction to EGT, this book gives a brief overview of the main statistical physics tools (such as phase transitions and the Ising model) and computational strategies for simulating evolutionary games (such as Monte Carlo algorithms on lattices). This book will appeal to students and researchers in this burgeoning field of complex systems.

This 2005 book investigates many topics in natural selection within the context of Darwinian dynamics and evolutionary game theory.

This book offers a holistic framework to study behavior and evolutionary dynamics in large-scale, decentralized, and heterogeneous crowd networks. In the emerging crowd cyber-ecosystems, millions of deeply connected individuals, smart devices, government agencies, and enterprises actively interact with each other and influence each other’s decisions. It is crucial to understand such intelligent entities’ behaviors and to study their strategic interactions in order to provide important guidelines on the design of reliable networks capable of predicting and preventing detrimental events with negative impacts on our society and economy. This book reviews the fundamental methodologies to study user interactions and evolutionary dynamics in crowd networks and discusses recent advances in this emerging interdisciplinary research field. Using information diffusion over social networks as an example, it presents a thorough investigation of the impact of user behavior on the network evolution process and demonstrates how this can help improve network performance. Intended for graduate students and researchers from various disciplines, including but not limited to, data science, networking, signal processing, complex systems, and economics, the book encourages researchers in related research fields to explore the many untouched areas in this domain, and ultimately to design crowd networks with efficient, effective, and reliable services.

This book aims to theoretically and empirically enrich the GVC accounting framework with statistical physics and complex network theory from the perspective of econophysics, thus adding up to the existing theories. Besides, it also aims at capturing the essences of network models such as topological complexity, hierarchy, transmissibility, interaction, and causality and reflecting the objective interrelations among economies or between economies and economic systems on the GVC, so as to reveal the inherent evolution of the cross-regional and even global economic systems.

This book discusses the study and analysis of the physical aspects of social systems and models, inspired by the analogy with familiar models of physical systems and possible applications of statistical physics tools. Unlike the traditional analysis of the physics of macroscopic many-body or condensed matter systems, which is now an established and mature subject, the upsurge in the physical analysis and modelling of social systems, which are clearly many-body dynamical systems, is a recent phenomenon. Though the major developments in sociophysics have taken place only recently, the earliest attempts of proposing "Social Physics" as a discipline are more than one and a half centuries old. Various developments in the mainstream physics of condensed matter systems have inspired and induced the recent growth of sociophysical analysis and models. In spite of the tremendous efforts of many scientists in recent years, the subject is still in its infancy and major challenges are yet to be taken up. An introduction to these challenges is the main motivation for this book.