The seminal 1989 work of Douglas and Paulsen on the theory of Hilbert modules over function algebras precipitated a number of major research efforts. This in turn led to some intriguing and valuable results, particularly in the areas of operator theory and functional analysis. With the field now beginning to blossom, the time has come to collect those results in one volume.

Written by two of the most active and often-cited researchers in the field, Analytic Hilbert Modules offers a clear, logical survey of recent developments, including advances made by authors and others. It provides much-needed insight into function theory of several variables and includes significant results published here for the first time in areas such as characteristic space theory, rigidity phenomena, the equivalence problem, Arveson modules, extension theory, and reproducing Hilbert spaces on n-dimensional complex space.

This textbook provides a one-semester introduction to mathematical economics for first year graduate and senior undergraduate students. Intended to fill the gap between typical liberal arts curriculum and the rigorous mathematical modeling of graduate study in economics, this text provides a concise introduction to the mathematics needed for core microeconomics, macroeconomics, and econometrics courses. Chapters 1 through 5 builds students' skills in formal proof, axiomatic treatment of linear algebra, and elementary vector differentiation. Chapters 6 and 7 present the basic tools needed for microeconomic analysis. Chapter 8 provides a quick introduction to (or review of) probability theory. Chapter 9 introduces dynamic modeling, applicable in advanced macroeconomics courses. The materials assume prerequisites in undergraduate calculus and linear algebra. Each chapter includes in-text exercises and a solutions manual, making this text ideal for self-study.

Game theory involves multi-person decision making and differential dynamic game theory has been widely applied to n-person decision making problems, which are stimulated by a vast number of applications. This book addresses the gap to discuss general stochastic n-person noncooperative and cooperative game theory with wide applications to control systems, signal processing systems, communication systems, managements, financial systems, and biological systems. H game strategy, n-person cooperative and noncooperative game strategy are discussed for linear and nonlinear stochastic systems along with some computational algorithms developed to efficiently solve these game strategies.

This book deals with nonsmooth structures arising within the optimization setting. It considers four optimization problems, namely, mathematical programs with complementarity constraints, general semi-infinite programming problems, mathematical programs with vanishing constraints and bilevel optimization. The author uses the topological approach and topological invariants of corresponding feasible sets are investigated. Moreover, the critical point theory in the sense of Morse is presented and parametric and stability issues are considered. The material progresses systematically and establishes a comprehensive theory for a rather broad class of optimization problems tailored to their particular type of nonsmoothness. Topological Aspects of Nonsmooth Optimization will benefit researchers and graduate students in applied mathematics, especially those working in optimization theory, nonsmooth analysis, algebraic topology and singularity theory.

Computationally-intensive tools play an increasingly important role in financial decisions. Many financial problems-ranging from asset allocation to risk management and from option pricing to model calibration-can be efficiently handled using modern computational techniques. Numerical Methods and Optimization in Finance presents such computational techniques, with an emphasis on simulation and optimization, particularly so-called heuristics. This book treats quantitative analysis as an essentially computational discipline in which applications are put into software form and tested empirically. This revised edition includes two new chapters, a self-contained tutorial on implementing and using heuristics, and an explanation of software used for testing portfolio-selection models. Postgraduate students, researchers in programs on quantitative and computational finance, and practitioners in banks and other financial companies can benefit from this second edition of Numerical Methods and Optimization in Finance.

This is the third volume of the "Handbook of Game Theory with Economic Applications." Since the publication of multi-Volume 1 a decade ago, game theory has continued to develop at a furious pace, and today it is the dominant tool in economic theory. The three volumes together cover the fundamental theoretical aspects, a wide range of applications to economics, several chapters on applications to political science and individual chapters on applications to disciplines as diverse as evolutionary biology, computer science, law, psychology and ethics. The authors are the most eminent practitioners in the field, including three Nobel Prize winners.

The topics covered in the present volume include strategic ("Nash") equilibrium; incomplete information; two-person non-zero-sum games; noncooperative games with a continuum of players; stochastic games; industrial organization; bargaining, inspection; economic history; the Shapley value and its applications to perfectly competitive economies, to taxation, to public goods and to fixed prices; political science; law mechanism design; and game experimentation.

This book is a collection of certain lectures given at the Economics Department at Stanford University on the game theory. It contains material on this theory of rational behavior of people with nonidentical interests whose area of application includes economics, politics, and war.

This book presents the huge variety of current contributions of game theory to economics. The impressive contributions fall broadly into two categories. Some lay out in a jargon free manner a particular branch of the theory, the evolution of one of its concepts, or a problem, that runs through its development. Others are original pieces of work that are significant to game theory as a whole.
After taking the reader through a concise history of game theory, the contributions include such themes as:
*the connections between Von Neumann's mathematical game theory and the domain assigned to him today
*the strategic use of information by game players
*the problem of the coordination of strategic choices between independent players
*cooperative games and their place within the literature of games plus new developments in non-cooperative games
*possible applications for game theory in industrial and financial economics differential qualitative games and entry dissuasion.

eBook available with sample pages: 0203167406

This comprehensive volume covers a wide range of duality topics ranging from simple ideas in network flows to complex issues issues in non-convex optimization and multicriteria problems. In addition, it examines duality in the context of variational inequalities and vector variational inequalities as generalizations to optimization. Duality in Optimization and Variational Inequalities is intended for researchers and practitioners of optimization with the aim of enhancing their understanding of duality and offers a wider appreciation of optimality conditions in various scenarios and under different assumptions. It will enable the reader to use duality to devise more effective computational methods, and to aid more meaningful interpretation of optimization and variational inequality problems.

The genre of adventure games is frequently overlooked. Lacking the constantly-evolving graphics and graphic violence of their counterparts in first-person and third-person shooters or role-playing games, they are often marketed to and beloved by players outside of mainstream game communities. While often forgotten by both the industry and academia, adventure games have had (and continue to have) a surprisingly wide influence on contemporary games, in categories including walking simulators, hidden object games, visual novels, and bestselling titles from companies like Telltale and Campo Santo. In this examination of heirs to the genre's legacy, the authors examine the genre from multiple perspectives, connecting technical analysis with critical commentary and social context. This will be the first book to consider this important genre from a comprehensive and transdisciplinary perspective. Drawing upon methods from platform studies, software studies, media studies, and literary studies, they reveal the genre's ludic and narrative origins and patterns, where character (and the player's embodiment of a character) is essential to the experience of play and the choices within a game. A deep structural analysis of adventure games also uncovers an unsteady balance between sometimes contradictory elements of story, exploration, and puzzles: with different games and creators employing a multitude of different solutions to resolving this tension.

Social and Economic Networks in Cooperative Game Theory presents a coherent overview of theoretical literature that studies the influence and formation of networks in social and economic situations in which the relations between participants who are not included in a particular participant's network are not of consequence to this participant. The material is organized in two parts. In Part I the authors concentrate on the question how network structures affect economic outcomes. Part II of the book presents the formation of networks by agents who engage in a network-formation process to be able to realize the possible gains from cooperation.

A pioneering look at the fundamental role of logic in optimization and constraint satisfaction

While recent efforts to combine optimization and constraint satisfaction have received considerable attention, little has been said about using logic in optimization as the key to unifying the two fields. Logic-Based Methods for Optimization develops for the first time a comprehensive conceptual framework for integrating optimization and constraint satisfaction, then goes a step further and shows how extending logical inference to optimization allows for more powerful as well as flexible modeling and solution techniques. Designed to be easily accessible to industry professionals and academics in both operations research and artificial intelligence, the book provides a wealth of examples as well as elegant techniques and modeling frameworks ready for implementation. Timely, original, and thought-provoking, Logic-Based Methods for Optimization:

• Demonstrates the advantages of combining the techniques in problem solving
• Offers tutorials in constraint satisfaction/constraint programming and logical inference
• Clearly explains such concepts as relaxation, cutting planes, nonserial dynamic programming, and Bender’s decomposition
• Reviews the necessary technologies for software developers seeking to combine the two techniques
• Features extensive references to important computational studies
• And much more

Vanderschraaf develops a new theory of game theory equilibrium selection in this book. The new theory defends general correlated equilibrium concepts and suggests a new analysis of convention.

This book covers the issues related to optimization of engineering and management problems using soft computing techniques with an industrial outlook. It covers a broad area related to real life complex decision making problems using a heuristics approach. It also explores a wide perspective and future directions in industrial engineering research on a global platform/scenario. The book highlights the concept of optimization, presents various soft computing techniques, offers sample problems, and discusses related software programs complete with illustrations. Features Explains the concept of optimization and relevance to soft computing techniques towards optimal solution in engineering and management Presents various soft computing techniques Offers problems and their optimization using various soft computing techniques Discusses related software programs, with illustrations Provides a step-by-step tutorial on how to handle relevant software for obtaining the optimal solution to various engineering problems

This volume presents a particular aspect of control theory-stabilization of programmed motion. Methods of the construction and synthesis of stabilizing controls are introduced together with original results and useful examples. The problem of optimal stabilization control synthesis is solved for linear systems of difference equations with quadratic quality criterion.

The Unpredictability of Gameplay explores the many forms of unpredictability in games and proposes a comprehensive theoretical framework for understanding and categorizing non-deterministic game mechanics. Rather than viewing all game mechanics with unpredictable outcomes as a single concept, Mark R. Johnson develops a three-part typology for such mechanics, distinguishing between randomness, chance, and luck in gameplay, assessing games that range from grand strategy and MMORPGs to slot machines and card games. He also explores forms of unanticipated unpredictability, where elements of games fail to function as intended and create new forms of gameplay in the process. Covering a range of game concepts using these frameworks, The Unpredictability of Gameplay then explores three illustrative case studies: 1) procedural generation, 2) replay value and grinding, and 3) player-made practices designed to reduce the level of luck in non-deterministic games. Throughout, Johnson demonstrates the importance of looking more deeply at unpredictability in games and game design and the various ways in which unpredictability manifests while offering an invaluable tool for game scholars and game designers seeking to integrate unpredictability into their work.

Game theory explores situations in which agents interact strategically and provides a useful foundation for studying many traditional industrial organization topics. This approach has also enabled the emergence of new areas of enquiry including law and economics, networks, the digital economy, auctions, experimental game theory and many others. This second volume of the Handbook includes original contributions by experts in the field. It provides up-to-date surveys of the most relevant applications of game theory to industrial organization. The book covers both classical and industrial organization topics such as mergers in markets with homogeneous and differentiated goods, leniency and coordinated effects in cartels and mergers, static and dynamic contests, consumer search and product safety, strategic delegation, platforms and network effects, auctions, environmental and resource economics, intellectual property, healthcare, corruption, experimental industrial organization, and empirical models of research and development. Authoritative and engaging, this unique Handbook will be an indispensable resource for all serious academics, researchers and students of industrial economics and game theory. Contributors incude: S. Anderson, A. Barge-Gil, P. Belleflamme, J. Brandts, R. Burguet, L. Corchon, A. Daughety, N. Fabra, R. Fauli-Oller, J.-J. Ganuza, M.l. Gonzalez Maestre, A. Hernando-Veciana, M. Hoffmann, E. Huergo, M. Kopel, L. Lambertini, A. Lopez, M. Marini, C. Marvao, E. Maskin, J.G. Montalvo, L. Moreno, M. Motta, P. Olivella, M. Peitz, M. Pezzino, M. Polo, J. Potters, J. Reinganum, R. Renault, G. Rota Preziosi, J. Sandonis, M. Serena, G. Spagnolo

In recent years, auctions have become an important field and many markets have designed new and sophisticated auction models to assign different types of items. The prime goal of this book is to set an organized classification of the main auction mechanisms in a way that readers can understand the importance of auction design and the advantages and drawbacks of each model. Given the relevance of the subject, there is a great volume of research about this topic. Nevertheless, most of these contributions use complex mathematical language difficult to understand for the average reader. In this book, the authors summarize the main ideas of the auction theory and explain them with simple language and plenty of examples. This book is a good starting point for any researcher interested in embracing the auction design as it also includes numerous real-world examples to engage the reader in the topic. "This book fills an important gap by making the main ideas and findings of auction research accessible." Professor Paul Milgrom, Department of Economics, Stanford University.

Unifies the field of optimization with a few geometric principles.

The number of books that can legitimately be called classics in their fields is small indeed, but David Luenberger's Optimization by Vector Space Methods certainly qualifies. Not only does Luenberger clearly demonstrate that a large segment of the field of optimization can be effectively unified by a few geometric principles of linear vector space theory, but his methods have found applications quite removed from the engineering problems to which they were first applied. Nearly 30 years after its initial publication, this book is still among the most frequently cited sources in books and articles on financial optimization.

The book uses functional analysis —the study of linear vector spaces —to impose simple, intuitive interpretations on complex, infinite-dimensional problems. The early chapters offer an introduction to functional analysis, with applications to optimization. Topics addressed include linear space, Hilbert space, least-squares estimation, dual spaces, and linear operators and adjoints. Later chapters deal explicitly with optimization theory, discussing

• Optimization of functionals
• Global theory of constrained optimization
• Local theory of constrained optimization
• Iterative methods of optimization.

End-of-chapter problems constitute a major component of this book and come in two basic varieties. The first consists of miscellaneous mathematical problems and proofs that extend and supplement the theoretical material in the text; the second, optimization problems, illustrates further areas of application and helps the reader formulate and solve practical problems.

For professionals and graduate students in engineering, mathematics, operations research, economics, and business and finance, Optimization by Vector Space Methods is an indispensable source of problem-solving tools.

This book describes the development of innovative non-centralized optimization-based control schemes to solve economic dispatch problems of large-scale energy systems. Particularly, it focuses on communication and cooperation processes of local controllers, which are integral parts of such schemes. The economic dispatch problem, which is formulated as a convex optimization problem with edge-based coupling constraints, is solved by using methodologies in distributed optimization over time-varying networks, together with distributed model predictive control, and system partitioning techniques. At first, the book describes two distributed optimization methods, which are iterative and require the local controllers to exchange information with each other at each iteration. In turn, it shows that the sequence produced by these methods converges to an optimal solution when some conditions, which include how the controllers must communicate and cooperate, are satisfied. Further, it proposes an information exchange protocol to cope with possible communication link failures. Finally, the proposed distributed optimization methods are extended to the cases with random communication networks and asynchronous updates. Overall, this book presents a set of improved predictive control and distributed optimization methods, together with a rigorous mathematical analysis of each proposed algorithms. It describes a comprehensive approach to cope with communication and cooperation issues of non-centralized control schemes and show how the improved schemes can be successfully applied to solve the economic dispatch problems of large-scale energy systems.

This volume features recent development and techniques in evolution equations by renown experts in the field. Each contribution emphasizes the relevance and depth of this important area of mathematics and its expanding reach into the physical, biological, social, and computational sciences as well as into engineering and technology. The reader will find an accessible summary of a wide range of active research topics, along with exciting new results. Topics include: Impulsive implicit Caputo fractional q-difference equations in finite and infinite dimensional Banach spaces; optimal control of averaged state of a population dynamic model; structural stability of nonlinear elliptic p(u)-Laplacian problem with Robin-type boundary condition; exponential dichotomy and partial neutral functional differential equations, stable and center-stable manifolds of admissible class; global attractor in Alpha-norm for some partial functional differential equations of neutral and retarded type; and more. Researchers in mathematical sciences, biosciences, computational sciences and related fields, will benefit from the rich and useful resources provided. Upper undergraduate and graduate students may be inspired to contribute to this active and stimulating field.

This book is devoted to the development of optimal control theory for finite dimensional systems governed by deterministic and stochastic differential equations driven by vector measures. The book deals with a broad class of controls, including regular controls (vector-valued measurable functions), relaxed controls (measure-valued functions) and controls determined by vector measures, where both fully and partially observed control problems are considered. In the past few decades, there have been remarkable advances in the field of systems and control theory thanks to the unprecedented interaction between mathematics and the physical and engineering sciences. Recently, optimal control theory for dynamic systems driven by vector measures has attracted increasing interest. This book presents this theory for dynamic systems governed by both ordinary and stochastic differential equations, including extensive results on the existence of optimal controls and necessary conditions for optimality. Computational algorithms are developed based on the optimality conditions, with numerical results presented to demonstrate the applicability of the theoretical results developed in the book. This book will be of interest to researchers in optimal control or applied functional analysis interested in applications of vector measures to control theory, stochastic systems driven by vector measures, and related topics. In particular, this self-contained account can be a starting point for further advances in the theory and applications of dynamic systems driven and controlled by vector measures.

This book presents Martin Shubik's important contribution to the development of game theory, and shows how game theory methods can be used in the study of prices, money and financial institutions. After introducing the reader to his career and the influences which developed his research, Professor Martin Shubik addresses the price system considering issues such as competitive equilibrium, economic exchange and production. He explores the competitive price system and the emergence of money and financial systems to develop a theory of monetary and financial institutions. Specifically, he examines the role of money in the economy using both cooperative and non-cooperative solutions in game theory. Throughout the book Martin Shubik stresses that the value of games, which can be both played and analysed, provides an important link between theory and process and institutional studies. This book will be welcomed by economists, especially those interested in game theory, as well as by money and banking professionals.

Martin Nowak, one of the world's experts on evolution and game theory, working here with bestselling science writer Roger Highfield, turns an important aspect of evolutionary theory on its head to explain why cooperation, not competition, has always been the key to the evolution of complexity. In his first book written for a wide audience, this hugely influential scientist explains his cutting-edge research into the mysteries of cooperation, from the rise of multicellular life to Good Samaritans, and from cancer treatment to the success of large companies. With wit and clarity, and an eye to its huge implications, Nowak and Highfield make the case that cooperation, not competition, is the defining human trait. "SuperCooperators "will expand our understanding of evolution and provoke debate for years to come.

This book presents a comprehensive analysis of tax consequences in an oligopolistic market. It provides the reader with a systematic and precise way of understanding the research content of tax incidence. A major feature of the book is its analysis of tax incidence from both domestic and international oligopolies. Then, by examining various oligopoly models, it approaches the essence of domestic and multilateral tax issues. Starting with the general theory of commodity tax incidence in an oligopoly, the topics addressed in this book include tax reform, environmental regulation, and policy coordination in international oligopolies. In addition to the usual oligopoly model, managerial oligopoly, the public pricing problem for firms in an oligopoly, and mixed oligopoly are dealt with. By presenting individual issues and explaining the relevance of each topic, this book is highly recommended for readers interested in policymaking and the global market in relation to the interdisciplinary developments of public economics, regional economics, and international economics. This book is also valuable as an advanced textbook on applied economics.