Why do some games seem to be universal while others have a particular connection to the culture of the people playing them? Around the World in 80 Games is about the mathematics of chance, game theory, gamification, gaming strategies and computer games. Traversing the globe, Marcus du Sautoy looks at the genesis of games new and old, explores how to invent a good game and explains the fascination of a popular lockdown game. From the secrets of whist to hopscotch, Scrabble to Wordle. The most simple games endure: board games, card games and dice games have captivated us for centuries and the acclaimed mathematician and author of The Creativity Code (among many others) will once again bring mathematics to the fore with insight and aplomb in Around the World in 80 Games.

The Handbook of Experimental Game Theory offers a comprehensive analysis of the field, discussing foundational topics that are at the core of applied game theory. It highlights the nuances that scientific experiments have delivered to our understanding of strategic interactions among decision makers. Leading experts explore methodological considerations and games of complete and incomplete information to offer new directions for research in experimental game theory. Chapters demonstrate transformative behavioral research focused on classic topics in game theory such as cooperation and coordination games. Taking a scientific approach to the study of game theory, this innovative Handbook provides an insight into laboratory and field experiments that test game theoretic propositions and suggests new ways of modeling strategic behavior. It takes a forward-thinking position, addressing the challenges inherent in innovations surrounding the measurement of strategic behavior using experimental methods. This Handbook will prove to be a valuable resource for scholars and students who are looking to gain a broader understanding of experimental game theory and how to contribute to its advancement. It will also be of particular interest to researchers in experimental and behavioral economics.

Economic theory and philosophy have discussed concepts of fairness, but the criteria of fairness are in each case absolute: a situation is either fair or it is not. This book draws on these literatures to propose two criteria of relative fairness, and a hierarchical rule for the priority of application of these criteria, with a view to comparison of practicable alternatives in public policy. A veil-of-ignorance device of representation of rational fairness is used to argue that these criteria are normatively relevant. Applications to intergenerational fairness, fairness among regions in the context of migration, externalities and Pigovian taxes, to fair prices and wages, and to relative fairness in the status of racial and caste groups are sketched. The book is designed with real world public policy practice. Scholars with an interest in the economic evaluation of public policy will find this compelling book essential reading.

Bestselling author and worst-drawing artist Ben Orlin expands his oeuvre with this interactive collection of mathematical games. With 70-plus games, each taking a minute to learn and a lifetime to master, this treasure trove will delight, educate, and entertain. From beloved math popularizer Ben Orlin comes a masterfully compiled collection of dozens of playable mathematical games. This ultimate game chest draws on mathematical curios, childhood classics, and soon-to-be classics, each hand-chosen to be (1) fun, (2) thought-provoking, and (3) easy to play. With just paper, pens, and the occasional handful of coins, you and a partner can enjoy hours of fun-and hours of challenge. Orlin's sly humor, expansive knowledge, and so-bad-they're-good drawings show us how simple rules summon our best thinking. Games include: * Ultimate Tic-Tac-Toe * Sprouts * Battleship * Quantum Go Fish * Dots and Boxes * Black Hole * Order and Chaos * Sequencium * Paper Boxing * Prophecies * Arpeggios * Banker * Francoprussian Labyrinth * Cats and Dogs * And many more.

What is the origin of game preferences and payoffs, how are they aggregated and what are the implications of interdependent preferences? What is the importance of information for building game models? How can game models be used to analyse empirical cases? At the cutting edge of current modelling in international relations using non-cooperative game theory, this collection of original contributions from political scientists and economists explores some of the fundamental assumptions of game theory modelling. It includes a theory of game payoff formation, a theory of preference aggregation, thorough discussions of the effects of interdependence between preferences upon various game structures, in-depth analyses of the impact of incomplete information upon dynamic games of negotiation, and a study using differential games. Numerous illustrations, case studies and comparative case studies show the relevance of the theoretical debate. The chapters are organised to allow readers with a limited knowledge of game theory to develop their understanding of the fundamental issues. Containing theoretical discussion of the basic game theory assumptions - as well as means of going beyond them - Game Theory and International Relations will be welcomed by all those interested in the empirical application of game theory models in international relations.

The book titled "Optimization Techniques" is based on optimization techniques and O.R. related courses for undergraduate and postgraduate engineering and mathematics students of various universities as well as for researchers working on optimization problems. The main objective of the book is to acquaint and familiarize the readers with different types of optimization techniques, solving optimization problems, implementing computational techniques, abstracting mathematical results and proofs etc. The book gives a clear appreciation and good grasp over most of the currently available optimization techniques. Each method developed has been illustrated with solved examples. A set of exercises for self practice is given at the end of each chapter. A set of brief answer review questions relating to the finer detail of the topics discussed in each chapter preceding the set of exercises has been added to facilitate learning and enhance the value of the book.

Building on the success of the first edition, Game Theory and Public Policy, Second Edition provides a critical, selective review of key concepts in game theory with a view to their applications in public policy. The author further suggests modifications for some of the models (chiefly in cooperative game theory) to improve their applicability to economics and public policy. Roger McCain makes use of the analytical tools of game theory for the pragmatic purpose of identifying problems and exploring potential solutions, providing a toolkit for the analysis of public policy allowing for a clearer understanding of the public policy enterprise itself. His critical review of major topics from both cooperative and non-cooperative game theory includes less-known ideas and constructive proposals for new approaches. This revised edition features a new second half that focuses on biform games, combining cooperative and non-cooperative decisions in a simple and natural way to provide a working model of externalities that can be applied to issues such as monopoly policy and labor market policies. Drawing on comparatively well understood models in cooperative game theory and the author's own research on mathematical models of biform games, this unique approach and treatment of game theory, updated and expanded to stay on the cutting edge, will be a useful resource for students and scholars of economics and public policy, as well as for policymakers themselves.

Explores the history, business, and technology of video games, including social, political, and economic motivations Facilitates learning with clear objectives, key terms, illustrative timelines, color images, tables and graphs Highlights the technical specifications and key titles of all major game consoles, handhelds, personal computers, and mobile platforms Reinforces material with market summaries, reviews of breakthroughs and trends, as well as end-of-chapter activities and quizzes New content in every chapter, from the PC-98, MSX, Amstrad, and ZX Spectrum to expanded coverage on mobile gaming, virtual reality, Steam Deck, Nintendo Switch, Xbox Series X|S, and PlayStation 5

Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB (R), this textbook trains mathematical scientists and engineers for the next generation of scientific discovery by offering a broad overview of the growing intersection of data-driven methods, machine learning, applied optimization, and classical fields of engineering mathematics and mathematical physics. With a focus on integrating dynamical systems modeling and control with modern methods in applied machine learning, this text includes methods that were chosen for their relevance, simplicity, and generality. Topics range from introductory to research-level material, making it accessible to advanced undergraduate and beginning graduate students from the engineering and physical sciences. The second edition features new chapters on reinforcement learning and physics-informed machine learning, significant new sections throughout, and chapter exercises. Online supplementary material - including lecture videos per section, homeworks, data, and code in MATLAB (R), Python, Julia, and R - available on databookuw.com.

Game theory means rigorous strategic thinking. It s the art of anticipating your opponent s next moves, knowing full well that your rival is trying to do the same thing to you. Though parts of game theory involve simple common sense, much is counterintuitive, and it can only be mastered by developing a new way of seeing the world. Using a diverse array of rich case studies from pop culture, TV, movies, sports, politics, and history the authors show how nearly every business and personal interaction has a game-theory component to it. Mastering game theory will make you more successful in business and life, and this lively book is the key to that mastery."

Mathematical Puzzle Tales from Mount Olympus uses fascinating tales from Greek Mythology as the background for introducing mathematics puzzles to the general public. A background in high school mathematics will be ample preparation for using this book, and it should appeal to anyone who enjoys puzzles and recreational mathematics. Features: Combines the arts and science, and emphasizes the fact that mathematics straddles both domains. Great resource for students preparing for mathematics competitions, and the trainers of such students.

The sequential quadratic hamiltonian (SQH) method is a novel numerical optimization procedure for solving optimal control problems governed by differential models. It is based on the characterisation of optimal controls in the framework of the Pontryagin maximum principle (PMP). The SQH method is a powerful computational methodology that is capable of development in many directions. The Sequential Quadratic Hamiltonian Method: Solving Optimal Control Problems discusses its analysis and use in solving nonsmooth ODE control problems, relaxed ODE control problems, stochastic control problems, mixed-integer control problems, PDE control problems, inverse PDE problems, differential Nash game problems, and problems related to residual neural networks. This book may serve as a textbook for undergraduate and graduate students, and as an introduction for researchers in sciences and engineering who intend to further develop the SQH method or wish to use it as a numerical tool for solving challenging optimal control problems and for investigating the Pontryagin maximum principle on new optimisation problems. Feature Provides insight into mathematical and computational issues concerning optimal control problems, while discussing many differential models of interest in different disciplines. Suitable for undergraduate and graduate students and as an introduction for researchers in sciences and engineering. Accompanied by codes which allow the reader to apply the SQH method to solve many different optimal control and optimisation problems

Optimization is presented in most multivariable calculus courses as an application of the gradient, and while this treatment makes sense for a calculus course, there is much more to the theory of optimization. Optimization problems are generated constantly, and the theory of optimization has grown and developed in response to the challenges presented by these problems. This textbook aims to show readers how optimization is done in practice and help them to develop an appreciation for the richness of the theory behind the practice. Exercises, problems (including modeling and computational problems), and implementations are incorporated throughout the text to help students learn by doing. Python notes are inserted strategically to help readers complete computational problems and implementations. The Basics of Practical Optimization, Second Edition is intended for undergraduates who have completed multivariable calculus, as well as anyone interested in optimization. The book is appropriate for a course that complements or replaces a standard linear programming course.

Composites have been studied for more than 150 years, and interest in their properties has been growing. This classic volume provides the foundations for understanding a broad range of composite properties, including electrical, magnetic, electromagnetic, elastic and viscoelastic, piezoelectric, thermal, fluid flow through porous materials, thermoelectric, pyroelectric, magnetoelectric, and conduction in the presence of a magnetic field (Hall effect). Exact solutions of the PDEs in model geometries provide one avenue of understanding composites; other avenues include microstructure-independent exact relations satisfied by effective moduli, for which the general theory is reviewed; approximation formulae for effective moduli; and series expansions for the fields and effective moduli that are the basis of numerical methods for computing these fields and moduli. The range of properties that composites can exhibit can be explored either through the model geometries or through microstructure-independent bounds on the properties. These bounds are obtained through variational principles, analytic methods, and Hilbert space approaches. Most interesting is when the properties of the composite are unlike those of the constituent materials, and there has been an explosion of interest in such composites, now known as metamaterials. The Theory of Composites surveys these aspects, among others, and complements the new body of literature that has emerged since the book was written. It remains relevant today by providing historical background, a compendium of numerous results, and through elucidating many of the tools still used today in the analysis of composite properties. This book is intended for applied mathematicians, physicists, and electrical and mechanical engineers. It will also be of interest to graduate students.

Building on the pioneering work by the Nobel Memorial Laureate, John Nash, Professor Thomson has brought together a broad selection of seminal articles which analyse and discuss bargaining and the theory of cooperative games. Beginning with a distinguished collection of papers discussing the origins of game theory, this volume systematically explores its development as a tool to illuminate economic behaviour. It includes the work of highly accomplished academics whose discoveries over the years have shaped the direction of this subject. With his insightful introduction, the editor has ensured that this indispensable book is suitable for anyone with an interest in cooperative gaming.

Extremum Seeking through Delays and PDEs, the first book on the topic, expands the scope of applicability of the extremum seeking method, from static and finite-dimensional systems to infinite-dimensional systems. Readers will find: Numerous algorithms for model-free real-time optimization are developed and their convergence guaranteed. Extensions from single-player optimization to noncooperative games, under delays and pdes, are provided. The delays and pdes are compensated in the control designs using the pde backstepping approach, and stability is ensured using infinite-dimensional versions of averaging theory. Accessible and powerful tools for analysis. This book is intended for control engineers in all disciplines (electrical, mechanical, aerospace, chemical), mathematicians, physicists, biologists, and economists. It is appropriate for graduate students, researchers, and industrial users.

Designed for a proof-based course on linear algebra, this rigorous and concise textbook intentionally introduces vector spaces, inner products, and vector and matrix norms before Gaussian elimination and eigenvalues so students can quickly discover the singular value decomposition (SVD)-arguably the most enlightening and useful of all matrix factorizations. Gaussian elimination is then introduced after the SVD and the four fundamental subspaces and is presented in the context of vector spaces rather than as a computational recipe. This allows the authors to use linear independence, spanning sets and bases, and the four fundamental subspaces to explain and exploit Gaussian elimination and the LU factorization, as well as the solution of overdetermined linear systems in the least squares sense and eigenvalues and eigenvectors. This unique textbook also includes examples and problems focused on concepts rather than the mechanics of linear algebra. The problems at the end of each chapter and in an associated website encourage readers to explore how to use the notions introduced in the chapter in a variety of ways. Additional problems, quizzes, and exams will be posted on an accompanying website and updated regularly. The Less Is More Linear Algebra of Vector Spaces and Matrices is for students and researchers interested in learning linear algebra who have the mathematical maturity to appreciate abstract concepts that generalize intuitive ideas. The early introduction of the SVD makes the book particularly useful for those interested in using linear algebra in applications such as scientific computing and data science. It is appropriate for a first proof-based course in linear algebra.

This book covers using R for doing optimization, a key area of operations research, which has been applied to virtually every industry. The focus is on linear and mixed integer optimization. It uses an algebraic modeling approach for creating formulations that pairs naturally with an algebraic implementation in R. With the rapid rise of interest in data analytics, a data analytics platform is key. Working technology and business professionals need an awareness of the tools and language of data analysis. R reduces the barrier to entry for people to start using data analytics tools. Philosophically, the book emphasizes creating formulations before going into implementation. Algebraic representation allows for clear understanding and generalization of large applications, and writing formulations is necessary to explain and convey the modeling decisions made. Appendix A introduces R. Mathematics is used at the level of subscripts and summations Refreshers are provided in Appendix B. This book: * Provides and explains code so examples are relatively clear and self-contained. * Emphasizes creating algebraic formulations before implementing. * Focuses on application rather than algorithmic details. * Embodies the philosophy of reproducible research. * Uses open-source tools to ensure access to powerful optimization tools. * Promotes open-source: all materials are available on the author's github repository. * Demonstrates common debugging practices with a troubleshooting emphasis specific to optimization modeling using R. * Provides code readers can adapt to their own applications . This book can be used for graduate and undergraduate courses for students without a background in optimization and with varying mathematical backgrounds.

Explores the history, business, and technology of video games, including social, political, and economic motivations Facilitates learning with clear objectives, key terms, illustrative timelines, color images, tables and graphs Highlights the technical specifications and key titles of all major game consoles, handhelds, personal computers, and mobile platforms Reinforces material with market summaries, reviews of breakthroughs and trends, as well as end-of-chapter activities and quizzes New content in every chapter, from the PC-98, MSX, Amstrad, and ZX Spectrum to expanded coverage on mobile gaming, virtual reality, Steam Deck, Nintendo Switch, Xbox Series X|S, and PlayStation 5

Features Includes cutting edge applications in machine learning and data analytics. Suitable as a primary text for undergraduates studying linear algebra. Requires very little in the way of pre-requisites.

This original new book offers a comprehensive and engaging perspective on the theory of vertical differentiation. It enables the reader to grasp the key concepts and effects that product quality has both on firms' behaviour and market structure, and the ways in which this relationship has evolved. With contributions from prominent figures in the field, the book investigates a number of important topics, such as the choice of the optimal product range, profit sharing, the existence of equilibrium in duopoly games, positional effects attached to status goods, international trade, collusion, advertising and the dynamics of capital accumulation for quality improvement and product innovation. Using both static and dynamic approaches, these aspects are assessed in relation to the manifold issues of regulation, competition policy and trade policy. Product differentiation and its influence on consumer behaviour and the performance of firms is a core topic in the existing literature in the fields of industrial organization, international trade and economic growth. This book will be an essential read for researchers, students and professional scholars working in these areas, especially those with an interest in antitrust regulation.

This book provides different approaches used to analyze, draw attention, and provide an understanding of the advancements in the optimization field across the globe. It brings all of the latest methodologies, tools, and techniques related to optimization and industrial engineering into a single volume to build insights towards the latest advancements in various domains. Applications of Advanced Optimization Techniques in Industrial Engineering includes the basic concept of optimization, techniques, and applications related to industrial engineering. Concepts are introduced in a sequential way along with explanations, illustrations, and solved examples. The book goes on to explore applications of operations research and covers empirical properties of a variety of engineering disciplines. It presents network scheduling, production planning, industrial and manufacturing system issues, and their implications in the real world. The book caters to academicians, researchers, professionals in inventory analytics, business analytics, investment managers, finance firms, storage-related managers, and engineers working in engineering industries and data management fields.

Optimality Conditions in Convex Optimization explores an important and central issue in the field of convex optimization: optimality conditions. It brings together the most important and recent results in this area that have been scattered in the literature-notably in the area of convex analysis-essential in developing many of the important results in this book, and not usually found in conventional texts. Unlike other books on convex optimization, which usually discuss algorithms along with some basic theory, the sole focus of this book is on fundamental and advanced convex optimization theory. Although many results presented in the book can also be proved in infinite dimensions, the authors focus on finite dimensions to allow for much deeper results and a better understanding of the structures involved in a convex optimization problem. They address semi-infinite optimization problems; approximate solution concepts of convex optimization problems; and some classes of non-convex problems which can be studied using the tools of convex analysis. They include examples wherever needed, provide details of major results, and discuss proofs of the main results.

Individuals, firms, governments and nations behave strategically, for good and bad. Over the last few decades, game theory has been constructed and progressively refined to become the major tool used by social scientists to understand, predict and regulate strategic interaction among agents who often have conflicting interests. In the surprisingly anodyne jargon of the theory, they play games'. This book offers an introduction to the basic tools of game theory and an overview of a number of applications to real-world cases, covering the areas of economics, politics and international relations. Each chapter is accompanied by some suggestions about further reading.

Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. This text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data science. An introductory chapter demonstrates that many standard problems in data science can be formulated as optimization problems. Next, many fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization of smooth (especially convex) functions; the stochastic gradient method, a workhorse algorithm in machine learning; the coordinate descent approach; several key algorithms for constrained optimization problems; algorithms for minimizing nonsmooth functions arising in data science; foundations of the analysis of nonsmooth functions and optimization duality; and the back-propagation approach, relevant to neural networks.