Statistical Physics and Computational Methods for Evolutionary Game Theory

Statistical Physics and Computational Methods for Evolutionary Game Theory PDF

Author: Marco Alberto Javarone

Publisher: Springer

Published: 2018-01-11

Total Pages: 74

ISBN-13: 331970205X

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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.

Computational Statistical Physics

Computational Statistical Physics PDF

Author: K.-H. Hoffmann

Publisher: Springer Science & Business Media

Published: 2013-03-14

Total Pages: 312

ISBN-13: 3662048043

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In recent years statistical physics has made significant progress as a result of advances in numerical techniques. While good textbooks exist on the general aspects of statistical physics, the numerical methods and the new developments based on large-scale computing are not usually adequately presented. In this book 16 experts describe the application of methods of statistical physics to various areas in physics such as disordered materials, quasicrystals, semiconductors, and also to other areas beyond physics, such as financial markets, game theory, evolution, and traffic planning, in which statistical physics has recently become significant. In this way the universality of the underlying concepts and methods such as fractals, random matrix theory, time series, neural networks, evolutionary algorithms, becomes clear. The topics are covered by introductory, tutorial presentations.

Fundamentals of Evolutionary Game Theory and its Applications

Fundamentals of Evolutionary Game Theory and its Applications PDF

Author: Jun Tanimoto

Publisher: Springer

Published: 2015-10-23

Total Pages: 223

ISBN-13: 4431549625

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​This book both summarizes the basic theory of evolutionary games and explains their developing applications, giving special attention to the 2-player, 2-strategy game. This game, usually termed a "2×2 game” in the jargon, has been deemed most important because it makes it possible to posit an archetype framework that can be extended to various applications for engineering, the social sciences, and even pure science fields spanning theoretical biology, physics, economics, politics, and information science. The 2×2 game is in fact one of the hottest issues in the field of statistical physics. The book first shows how the fundamental theory of the 2×2 game, based on so-called replicator dynamics, highlights its potential relation with nonlinear dynamical systems. This analytical approach implies that there is a gap between theoretical and reality-based prognoses observed in social systems of humans as well as in those of animal species. The book explains that this perceived gap is the result of an underlying reciprocity mechanism called social viscosity. As a second major point, the book puts a sharp focus on network reciprocity, one of the five fundamental mechanisms for adding social viscosity to a system and one that has been a great concern for study by statistical physicists in the past decade. The book explains how network reciprocity works for emerging cooperation, and readers can clearly understand the existence of substantial mechanics when the term "network reciprocity" is used. In the latter part of the book, readers will find several interesting examples in which evolutionary game theory is applied. One such example is traffic flow analysis. Traffic flow is one of the subjects that fluid dynamics can deal with, although flowing objects do not comprise a pure fluid but, rather, are a set of many particles. Applying the framework of evolutionary games to realistic traffic flows, the book reveals that social dilemma structures lie behind traffic flow.

Advances in Dynamic and Evolutionary Games

Advances in Dynamic and Evolutionary Games PDF

Author: Frank Thuijsman

Publisher: Birkhäuser

Published: 2016-04-07

Total Pages: 330

ISBN-13: 3319280147

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This contributed volume considers recent advances in dynamic games and their applications, based on presentations given at the 16th Symposium of the International Society of Dynamic Games, held July 9-12, 2014, in Amsterdam. Written by experts in their respective disciplines, these papers cover various aspects of dynamic game theory including differential games, evolutionary games, and stochastic games. They discuss theoretical developments, algorithmic methods, issues relating to lack of information, and applications in areas such as biological or economical competition, stability in communication networks, and maintenance decisions in an electricity market, just to name a few. Advances in Dynamic and Evolutionary Games presents state-of-the-art research in a wide spectrum of areas. As such, it serves as a testament to the vitality and growth of the field of dynamic games and their applications. It will be of interest to an interdisciplinary audience of researchers, practitioners, and advanced graduate students.

Complexity and Artificial Markets

Complexity and Artificial Markets PDF

Author: Klaus Schredelseker

Publisher: Springer Science & Business Media

Published: 2008-07-30

Total Pages: 235

ISBN-13: 3540705562

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In recent years, agent-based simulation has become a widely accepted tool when dealing with complexity in economics and other social sciences. The contributions presented in this book apply agent-based methods to derive results from complex models related to market mechanisms, evolution, decision making, and information economics. In addition, the applicability of agent-based methods to complex problems in economics is discussed from a methodological perspective. The papers presented in this collection combine approaches from economics, finance, computer science, natural sciences, philosophy, and cognitive sciences.

Advances in Dynamic Game Theory

Advances in Dynamic Game Theory PDF

Author: Steffen Jorgensen

Publisher: Springer Science & Business Media

Published: 2007-04-13

Total Pages: 722

ISBN-13: 0817643990

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This collection of selected contributions gives an account of recent developments in dynamic game theory and its applications, covering both theoretical advances and new applications of dynamic games in such areas as pursuit-evasion games, ecology, and economics. Written by experts in their respective disciplines, the chapters include stochastic and differential games; dynamic games and their applications in various areas, such as ecology and economics; pursuit-evasion games; and evolutionary game theory and applications. The work will serve as a state-of-the art account of recent advances in dynamic game theory and its applications for researchers, practitioners, and advanced students in applied mathematics, mathematical finance, and engineering.

Evolutionary Games in Natural, Social, and Virtual Worlds

Evolutionary Games in Natural, Social, and Virtual Worlds PDF

Author: Daniel Friedman

Publisher: Oxford University Press

Published: 2016-02-01

Total Pages: 436

ISBN-13: 0199981175

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Over the last 25 years, evolutionary game theory has grown with theoretical contributions from the disciplines of mathematics, economics, computer science and biology. It is now ripe for applications. In this book, Daniel Friedman---an economist trained in mathematics---and Barry Sinervo---a biologist trained in mathematics---offer the first unified account of evolutionary game theory aimed at applied researchers. They show how to use a single set of tools to build useful models for three different worlds: the natural world studied by biologists; the social world studied by anthropologists, economists, political scientists and others; and the virtual world built by computer scientists and engineers. The first six chapters offer an accessible introduction to core concepts of evolutionary game theory. These include fitness, replicator dynamics, sexual dynamics, memes and genes, single and multiple population games, Nash equilibrium and evolutionarily stable states, noisy best response and other adaptive processes, the Price equation, and cellular automata. The material connects evolutionary game theory with classic population genetic models, and also with classical game theory. Notably, these chapters also show how to estimate payoff and choice parameters from the data. The last eight chapters present exemplary game theory applications. These include a new coevolutionary predator-prey learning model extending rock-paper-scissors; models that use human subject laboratory data to estimate learning dynamics; new approaches to plastic strategies and life cycle strategies, including estimates for male elephant seals; a comparison of machine learning techniques for preserving diversity to those seen in the natural world; analyses of congestion in traffic networks (either internet or highways) and the “price of anarchy”; environmental and trade policy analysis based on evolutionary games; the evolution of cooperation; and speciation. As an aid for instruction, a web site provides downloadable computational tools written in the R programming language, Matlab, Mathematica and Excel.

Statistical Network Genetics

Statistical Network Genetics PDF

Author: Rongling Wu

Publisher: Academic Press

Published: 2023-01-15

Total Pages: 225

ISBN-13: 9780323988018

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Statistical Network Genetics: Evolutionary Game Theory in Action offers an interdisciplinary integration of statistical genetics and evolutionary game theory using the latest data, codes, and computational functions. While classic statistical genetics attempts to identify and map individual key genes, proteins, or metabolites associated with complex traits, this book examines how each entity interacts with each other through this complex, yet well-orchestrated, set of networks for mediating phenotypic variation. Written by leading experts on game theory and statistical genetics, this book introduces elements from multiple disciplines, like community ecology, network theory, and physics theory, tying them in to statistical model examples. The book provides a platform for previously disjointed ideas and concepts of evolutionary game theory and its role in statistical genetics. It covers genetic and genomic networking across ecological, environmental, as well as evolutionary factors. Statistical Network Genetics: Evolutionary Game Theory in Action is the ideal resource for evolutionary and computational biologists, especially those seeking a thorough and current understanding of the connection to statistical genetics. Examines and describes state-of-the-art approaches for maximizing statistical genetic research Provides usable computer codes for readers to practice statistical methods described in the chapters Features expert analysis of high-dimensional data for linking genotypes to phenotypes, emphasizing the role of omics data to understanding phenotypic formation

Evolutionary Game Theory

Evolutionary Game Theory PDF

Author: J. McKenzie Alexander

Publisher: Cambridge University Press

Published: 2023-03-31

Total Pages: 115

ISBN-13: 1009380583

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Evolutionary game theory originated in population biology from the realisation that frequency-dependent fitness introduced a strategic element into evolution. Since its development, evolutionary game theory has been adopted by many social scientists, and philosophers, to analyse interdependent decision problems played by boundedly rational individuals. Its study has led to theoretical innovations of great interest for the biological and social sciences. For example, theorists have developed a number of dynamical models which can be used to study how populations of interacting individuals change their behaviours over time. In this introduction, this Element covers the two main approaches to evolutionary game theory: the static analysis of evolutionary stability concepts, and the study of dynamical models, their convergence behaviour and rest points. This Element also explores the many fascinating, and complex, connections between the two approaches.