This book surveys new algorithmic approaches and applications to natural and man-made disasters such as oil spills, hurricanes, earthquakes and wildfires. Based on the "Third International Conference on Dynamics of Disasters" held in Kalamata, Greece, July 2017, this Work includes contributions in evacuation logistics, disaster communications between first responders, disaster relief, and a case study on humanitarian logistics. Multi-disciplinary theories, tools, techniques and methodologies are linked with disasters from mitigation and preparedness to response and recovery. The interdisciplinary approach to problems in economics, optimization, government, management, business, humanities, engineering, medicine, mathematics, computer science, behavioral studies, emergency services, and environmental studies will engage readers from a wide variety of fields and backgrounds.

A Beautiful Mind is Sylvia Nasar's award-winning biography about the mystery of the human mind, the triumph over incredible adversity, and the healing power of love. At the age of thirty-one, John Nash, mathematical genius, suffered a devastating breakdown and was diagnosed with schizophrenia. Yet after decades of leading a ghost-like existence, he was to re-emerge to win a Nobel Prize and world acclaim. A Beautiful Mind has inspired the Oscar-winning film directed by Ron Howard and featuring Russell Crowe in the lead role of John Nash.

This well-thought-out book covers the fundamentals of nonlinear analysis, with a particular focus on variational methods and their applications. Starting from preliminaries in functional analysis, it expands in several directions such as Banach spaces, fixed point theory, nonsmooth analysis, minimax theory, variational calculus and inequalities, critical point theory, monotone, maximal monotone and pseudomonotone operators, and evolution problems.

Born of a belief that economic insights should not require much mathematical sophistication, this book proposes novel and parsimonious methods to incorporate ignorance and uncertainty into economic modeling, without complex mathematics. Economics has made great strides over the past several decades in modeling agents' decisions when they are incompletely informed, but many economists believe that there are aspects of these models that are less than satisfactory. Among the concerns are that ignorance is not captured well in most models, that agents' presumed cognitive ability is implausible, and that derived optimal behavior is sometimes driven by the fine details of the model rather than the underlying economics. Compte and Postlewaite lay out a tractable way to address these concerns, and to incorporate plausible limitations on agents' sophistication. A central aspect of the proposed methodology is to restrict the strategies assumed available to agents.

This book constitutes the thoroughly refereed proceedings of the Clausthal-Goettingen International Workshop on Simulation Science, held in Goettingen, Germany, in April 2017. The 16 full papers presented were carefully reviewed and selected from 40 submissions. The papers are organized in topical sections on simulation and optimization in networks, simulation of materials, distributed simulations.

Optimization methods play a central role in financial modeling. This textbook is devoted to explaining how state-of-the-art optimization theory, algorithms, and software can be used to efficiently solve problems in computational finance. It discusses some classical mean-variance portfolio optimization models as well as more modern developments such as models for optimal trade execution and dynamic portfolio allocation with transaction costs and taxes. Chapters discussing the theory and efficient solution methods for the main classes of optimization problems alternate with chapters discussing their use in the modeling and solution of central problems in mathematical finance. This book will be interesting and useful for students, academics, and practitioners with a background in mathematics, operations research, or financial engineering. The second edition includes new examples and exercises as well as a more detailed discussion of mean-variance optimization, multi-period models, and additional material to highlight the relevance to finance.

This book provides a concise introduction to convex duality in financial mathematics. Convex duality plays an essential role in dealing with financial problems and involves maximizing concave utility functions and minimizing convex risk measures. Recently, convex and generalized convex dualities have shown to be crucial in the process of the dynamic hedging of contingent claims. Common underlying principles and connections between different perspectives are developed; results are illustrated through graphs and explained heuristically. This book can be used as a reference and is aimed toward graduate students, researchers and practitioners in mathematics, finance, economics, and optimization. Topics include: Markowitz portfolio theory, growth portfolio theory, fundamental theorem of asset pricing emphasizing the duality between utility optimization and pricing by martingale measures, risk measures and its dual representation, hedging and super-hedging and its relationship with linear programming duality and the duality relationship in dynamic hedging of contingent claims

Dynamic games continue to attract strong interest from researchers interested in modelling competitive as well as conflict situations exhibiting an intertemporel aspect. Applications of dynamic games have proven to be a suitable methodology to study the behaviour of players (decision-makers) and to predict the outcome of such situations in many areas including engineering, economics, management science, military, biology and political science.

Dynamic Games Theory and Applications collects thirteen articles written by established researchers. It is an excellent reference for researchers and graduate students covering a wide range of emerging and revisited problems in both cooperative and non-cooperative games in different areas of applications, especially in economics and management science.

This brief introduces game- and decision-theoretical techniques for the analysis and design of resilient interdependent networks. It unites game and decision theory with network science to lay a system-theoretical foundation for understanding the resiliency of interdependent and heterogeneous network systems. The authors pay particular attention to critical infrastructure systems, such as electric power, water, transportation, and communications. They discuss how infrastructure networks are becoming increasingly interconnected as the integration of Internet of Things devices, and how a single-point failure in one network can propagate to other infrastructures, creating an enormous social and economic impact. The specific topics in the book include: * static and dynamic meta-network resilience game analysis and design; * optimal control of interdependent epidemics spreading over complex networks; and * applications to secure and resilient design of critical infrastructures. These topics are supported by up-to-date summaries of the authors' recent research findings. The authors then discuss the future challenges and directions in the analysis and design of interdependent networks and explain the role of multi-disciplinary research has in computer science, engineering, public policy, and social sciences fields of study. The brief introduces new application areas in mathematics, economics, and system and control theory, and will be of interest to researchers and practitioners looking for new approaches to assess and mitigate risks in their systems and enhance their network resilience. A Game- and Decision-Theoretic Approach to Resilient Interdependent Network Analysis and Design also has self-contained chapters, which allows for multiple levels of reading by anyone with an interest in game and decision theory and network science.

The world's best negotiators have moved beyond the conventional wisdom by utilising cutting-edge studies and real-world results. It's time you did too. For over twenty years, David Sally has been teaching the art of negotiation at leading business schools and to executives at top companies. Now, using insights from social psychology and game theory, he delivers the proven, clear, actionable advice you need to stay one step ahead. By studying great examples, from Machiavelli to Wall Street, Xi Jinping and Barack Obama, he explores how the game's masters navigate the field strategically, craftily, even emotionally. The best know every negotiation is different and that your tactics are, in part, determined by your opponent. One Step Ahead will make sure that you have what it takes to come out on top, no matter who you are facing across the table.

Game theory has revolutionised our understanding of industrial organisation and the traditional theory of the firm. Despite these advances, industrial economists have tended to rely on a restricted set of tools from game theory, focusing on static and repeated games to analyse firm structure and behaviour. Luca Lambertini, a leading expert on the application of differential game theory to economics, argues that many dynamic phenomena in industrial organisation (such as monopoly, oligopoly, advertising, R&D races) can be better understood and analysed through the use of differential games. After illustrating the basic elements of the theory, Lambertini guides the reader through the main models, spanning from optimal control problems describing the behaviour of a monopolist through to oligopoly games in which firms' strategies include prices, quantities and investments. This approach will be of great value to students and researchers in economics and those interested in advanced applications of game theory.

In contrast to mainstream economics, complexity theory conceives the economy as a complex system of heterogeneous interacting agents characterised by limited information and bounded rationality. Agent Based Models (ABMs) are the analytical and computational tools developed by the proponents of this emerging methodology. Aimed at students and scholars of contemporary economics, this book includes a comprehensive toolkit for agent-based computational economics, now quickly becoming the new way to study evolving economic systems. Leading scholars in the field explain how ABMs can be applied fruitfully to many real-world economic examples and represent a great advancement over mainstream approaches. The essays discuss the methodological bases of agent-based approaches and demonstrate step-by-step how to build, simulate and analyse ABMs and how to validate their outputs empirically using the data. They also present a wide set of applications of these models to key economic topics, including the business cycle, labour markets, and economic growth.

This book considers and builds on the main propositions regarding body similarity and the principles of nature versus artifacts in science. It also explores the design (matrix) power of the human, Material/Machine, Money & Information (3M&I) body with respect to productivity/gross domestic product (GDP). The book begins in 2009 with Weiner's cybernetics and describes Matsui's theory and dynamism concerning the basic equation of W = ZL and artifact formulation using matrix methods, such as Matsui's matrix equation (Matsui's ME). In his book Fundamentals and Principles of Artifacts Science: 3M&I-Body System, published by Springer in 2016, the author championed the white-box approach for 3M&I artifacts in contrast to Simon's artificial approach from 1969. Two principles, the Sandwich (waist) and Balancing theories, and their fundamental problems, were identified. This book now proposes a third principle: the fractal/harmonic-like structure of the cosmos and life types in space and time. The book further elaborates on the complexity of the 3M&I system and management in terms of enterprises, economics, nature, and other applications. Also, the domain of nature versus artifacts is highlighted, demonstrating the possibility of a white-box cybernetics-type robot. This fosters the realization of humanized and harmonic worlds that combine increased happiness and social productivity in an age increasingly dominated by technology.

This book explores the updated version of the GLOBAL algorithm which contains improvements for a local search algorithm and new Java implementations. Efficiency comparisons to earlier versions and on the increased speed achieved by the parallelization, are detailed. Examples are provided for students as well as researchers and practitioners in optimization, operations research, and mathematics to compose their own scripts with ease. A GLOBAL manual is presented in the appendix to assist new users with modules and test functions. GLOBAL is a successful stochastic multistart global optimization algorithm that has passed several computational tests, and is efficient and reliable for small to medium dimensional global optimization problems. The algorithm uses clustering to ensure efficiency and is modular in regard to the two local search methods it starts with, but it can also easily apply other local techniques. The strength of this algorithm lies in its reliability and adaptive algorithm parameters. The GLOBAL algorithm is free to download also in the earlier Fortran, C, and MATLAB implementations.

This book develops a machine-learning framework for predicting economic growth. It can also be considered as a primer for using machine learning (also known as data mining or data analytics) to answer economic questions. While machine learning itself is not a new idea, advances in computing technology combined with a dawning realization of its applicability to economic questions makes it a new tool for economists.

LEGOfied: Building Blocks as Media provides a multi-faceted exploration of LEGO fandom, addressing a blindspot in current accounts of LEGO and an emerging area of interest to media scholars: namely, the role of hobbyist enthusiasts and content producers in LEGO's emergence as a ubiquitous transmedia franchise. This book examines a range of LEGO hobbyism and their attendant forms of mediated self-expression and identity (their "technicities"): artists, aspiring Master Builders, collectors, and entrepreneurs who refashion LEGO bricks into new commodities (sets, tchotchkes, and minifigures). The practices and perspectives that constitute this diverse scene lie at the intersection of multiple transformations in contemporary culture, including the shifting relationships between culture industries and the audiences that form their most ardent consumer base, but also the emerging forms of entrepreneurialism, professionalization, and globalization that characterize the burgeoning DIY movement. What makes this a compelling project for media scholars is its mutli-dimensional articulation of how LEGO functions not just as a toy, cultural icon, or as transmedia franchise, but as a media platform. LEGOfied is centered around their shared experiences, qualitative observations, and semi-structured interviews at a number of LEGO hobbyist conventions. Working outwards from these conventions, each chapter engages additional modes of inquiry-media archaeology, aesthetics, posthumanist philosophy, feminist media studies, and science and technology studies-to explore the origins, permutations and implications of different aspects of the contemporary LEGO fandom scene.

Decision-making in the face of uncertainty is a significant challenge in machine learning, and the multi-armed bandit model is a commonly used framework to address it. This comprehensive and rigorous introduction to the multi-armed bandit problem examines all the major settings, including stochastic, adversarial, and Bayesian frameworks. A focus on both mathematical intuition and carefully worked proofs makes this an excellent reference for established researchers and a helpful resource for graduate students in computer science, engineering, statistics, applied mathematics and economics. Linear bandits receive special attention as one of the most useful models in applications, while other chapters are dedicated to combinatorial bandits, ranking, non-stationary problems, Thompson sampling and pure exploration. The book ends with a peek into the world beyond bandits with an introduction to partial monitoring and learning in Markov decision processes.

This book presents eleven classic papers by the late Professor Suzanne Scotchmer with introductions by leading economists and legal scholars. This book introduces Scotchmer's life and work; analyses her pioneering contributions to the economics of patents and innovation incentives, with a special focus on the modern theory of cumulative innovation; and describes her pioneering work on law and economics, evolutionary game theory, and general equilibrium/club theory. This book also provides a self-contained introduction to students who want to learn more about the various fields that Professor Scotchmer worked in, with a particular focus on patent incentives and cumulative innovation.

How do people living in small groups without money, markets, police and rigid social classes develop norms of economic and social cooperation that are sustainable over time? This book addresses this fundamental question and explains the origin, structure and spread of stateless societies. Using insights from game theory, ethnography and archaeology, Stanish shows how ritual - broadly defined - is the key. Ritual practices encode elaborate rules of behavior and are ingenious mechanisms of organizing society in the absence of coercive states. As well as asking why and how people choose to co-operate, Stanish also provides the theoretical framework to understand this collective action problem. He goes on to highlight the evolution of cooperation with ethnographic and archaeological data from around of the world. Merging evolutionary game theory concepts with cultural evolutionary theory, this book will appeal to those seeking a transdisciplinary approach to one of the greatest problems in human evolution.

Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. With a simple, unified approach, and with attention to real-time implementation, it covers predictive control theory including the stability, feasibility, and robustness of MPC controllers. The theory of explicit MPC, where the nonlinear optimal feedback controller can be calculated efficiently, is presented in the context of linear systems with linear constraints, switched linear systems, and, more generally, linear hybrid systems. Drawing upon years of practical experience and using numerous examples and illustrative applications, the authors discuss the techniques required to design predictive control laws, including algorithms for polyhedral manipulations, mathematical and multiparametric programming and how to validate the theoretical properties and to implement predictive control policies. The most important algorithms feature in an accompanying free online MATLAB toolbox, which allows easy access to sample solutions. Predictive Control for Linear and Hybrid Systems is an ideal reference for graduate, postgraduate and advanced control practitioners interested in theory and/or implementation aspects of predictive control.

The main goal of this book is to show how to modify and optimize the properties of the damping matrix in order to find the most beneficial way of adding damping to a given mechanical system. To this end, a two-degree-of-freedom model of disc brake is analyzed to gain insight into the fundamental physical behavior of damping. In addition, more realistic, high-dimensional finite element brake models are studied and optimized for stability.

Fascinating, accessible introduction to enormously important intellectual system with numerous applications to social, economic, political problems. Newly revised edition offers overview of game theory, then lucid coverage of the two-person zero-sum game with equilibrium points; the general, two-person zero-sum game; utility theory; other topics. Problems at start of each chapter. Foreword to First Edition by Oskar Morgenstern. Bibliography.

Classical decision theory evaluates entire worlds, specified so as to include everything a decision-maker cares about. Thus applying decision theory requires performing computations far beyond an ordinary decision-maker's ability. In this book Paul Weirich explains how individuals can simplify and streamline their choices. He shows how different 'parts' of options (intrinsic, temporal, spatiotemporal, causal) are separable, so that we can know what difference one part makes to the value of an option, regardless of what happens in the other parts. He suggests that the primary value of options is found in basic intrinsic attitudes towards outcomes: desires, aversions, or indifferences. And using these two facts he argues that we need only compare small parts of the options we face in order to make a rational decision. This important book will interest readers in decision theory, economics, and the behavioral sciences.

This book on constrained optimization is novel in that it fuses these themes: * use examples to introduce general ideas; * engage the student in spreadsheet computation; * survey the uses of constrained optimization;. * investigate game theory and nonlinear optimization, * link the subject to economic reasoning, and * present the requisite mathematics. Blending these themes makes constrained optimization more accessible and more valuable. It stimulates the student's interest, quickens the learning process, reveals connections to several academic and professional fields, and deepens the student's grasp of the relevant mathematics. The book is designed for use in courses that focus on the applications of constrained optimization, in courses that emphasize the theory, and in courses that link the subject to economics.

This book presents mathematical models and numerical simulations of crowd dynamics. The core topic is the development of a new multiscale paradigm, which bridges the microscopic and macroscopic scales taking the most from each of them for capturing the relevant clues of complexity of crowds. The background idea is indeed that most of the complex trends exhibited by crowds are due to an intrinsic interplay between individual and collective behaviors. The modeling approach promoted in this book pursues actively this intuition and profits from it for designing general mathematical structures susceptible of application also in fields different from the inspiring original one. The book considers also the two most traditional points of view: the microscopic one, in which pedestrians are tracked individually and the macroscopic one, in which pedestrians are assimilated to a continuum. Selected existing models are critically analyzed. The work is addressed to researchers and graduate students.