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| computer science and economics: Mathematical Economics Kelvin Lancaster, 2012-10-10 Graduate-level text provides complete and rigorous expositions of economic models analyzed primarily from the point of view of their mathematical properties, followed by relevant mathematical reviews. Part I covers optimizing theory; Parts II and III survey static and dynamic economic models; and Part IV contains the mathematical reviews, which range fromn linear algebra to point-to-set mappings. |
| computer science and economics: Advances in Intelligent Systems, Computer Science and Digital Economics Zhengbing Hu, Sergey Petoukhov, Matthew He, 2020-01-23 This book comprises high-quality, refereed research papers presented at the 2019 International Symposium on Computer Science, Digital Economy and Intelligent Systems (CSDEIS2019): The symposium, held in Moscow, Russia, on 4–6 October 2019, was organized jointly by Moscow State Technical University and the International Research Association of Modern Education and Computer Science. The book discusses the state of the art in areas such as computer science and its technological applications; intelligent systems and intellectual approaches; and digital economics and methodological approaches. It is an excellent reference resource for researchers, undergraduate and graduate students, engineers, and management practitioners interested in computer science and its applications in engineering and management. |
| computer science and economics: Handbook of Research on Nature-Inspired Computing for Economics and Management Rennard, Jean-Philippe, 2006-09-30 This book provides applications of nature inspired computing for economic theory and practice, finance and stock-market, manufacturing systems, marketing, e-commerce, e-auctions, multi-agent systems and bottom-up simulations for social sciences and operations management--Provided by publisher. |
| computer science and economics: Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Policy and Global Affairs, Board on Higher Education and Workforce, Committee on the Growth of Computer Science Undergraduate Enrollments, 2018-04-28 The field of computer science (CS) is currently experiencing a surge in undergraduate degree production and course enrollments, which is straining program resources at many institutions and causing concern among faculty and administrators about how best to respond to the rapidly growing demand. There is also significant interest about what this growth will mean for the future of CS programs, the role of computer science in academic institutions, the field as a whole, and U.S. society more broadly. Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments seeks to provide a better understanding of the current trends in computing enrollments in the context of past trends. It examines drivers of the current enrollment surge, relationships between the surge and current and potential gains in diversity in the field, and the potential impacts of responses to the increased demand for computing in higher education, and it considers the likely effects of those responses on students, faculty, and institutions. This report provides recommendations for what institutions of higher education, government agencies, and the private sector can do to respond to the surge and plan for a strong and sustainable future for the field of CS in general, the health of the institutions of higher education, and the prosperity of the nation. |
| computer science and economics: Internet Economics Lee W. McKnight, Joseph P. Bailey, 1998 The Internet has rapidly become an important element of the economic system. The lack of accepted metrics for economic analysis of Internet transactions is therefore increasingly problematic. This book, one of the first to bring together research on Internet engineering and economics, attempts to establish such metrics. The chapters, which developed out of a 1995 workshop held at MIT, include architectural models and analyses of Internet usage, as well as alternative pricing policies. The book is organized into six sections: 1) Introduction to Internet Economics, 2) The Economics of the Internet, 3) Interconnection and Multicast Economics, 4) Usage Sensitive Pricing, 5) Internet Commerce, and 6) Internet Economics and Policy. Contributors Loretta Anania, Joseph P. Bailey, Nevil Brownlee, David Carver, David Clark, David W. Crawford, Ketil Danielsen, Deborah Estrin, Branko Gerovac, David Gingold, Jiong Gong, Alok Gupta, Shai Herzog, Clark Johnson, Martyne M. Hallgren, Frank P. Kelly, Charlie Lai, Alan K. McAdams, Jeffrey K. MacKie-Mason, Lee W. McKnight, Gennady Medvinsky, Liam Murphy, John Murphy, B. Clifford Neuman, Jon M. Peha, Joseph Reagle, Mitrabarun Sarkar, Scott Shenker, Marvin A. Sirbu, Richard Jay Solomon, Padmanabhan Srinagesh, Dale O. Stahl, Hal R. Varian, Qiong Wang, Martin Weiss, Andrew B. Whinston |
| computer science and economics: Economic Dynamics, second edition John Stachurski, 2022-08-16 The second edition of a rigorous and example-driven introduction to topics in economic dynamics that emphasizes techniques for modeling dynamic systems. This text provides an introduction to the modern theory of economic dynamics, with emphasis on mathematical and computational techniques for modeling dynamic systems. Written to be both rigorous and engaging, the book shows how sound understanding of the underlying theory leads to effective algorithms for solving real-world problems. The material makes extensive use of programming examples to illustrate ideas, bringing to life the abstract concepts in the text. Key topics include algorithms and scientific computing, simulation, Markov models, and dynamic programming. Part I introduces fundamentals and part II covers more advanced material. This second edition has been thoroughly updated, drawing on recent research in the field. New for the second edition: “Programming-language agnostic” presentation using pseudocode. New chapter 1 covering conceptual issues concerning Markov chains such as ergodicity and stability. New focus in chapter 2 on algorithms and techniques for program design and high-performance computing. New focus on household problems rather than optimal growth in material on dynamic programming. Solutions to many exercises, code, and other resources available on a supplementary website. |
| computer science and economics: Beyond the Worst-Case Analysis of Algorithms Tim Roughgarden, 2021-01-14 Introduces exciting new methods for assessing algorithms for problems ranging from clustering to linear programming to neural networks. |
| computer science and economics: Complexity Theory, Game Theory, and Economics Tim Roughgarden, 2020-03-02 This monograph comprises a series of ten lectures divided into two parts. Part 1 focuses on the communication and computational complexity of computing an (approximate) Nash equilibrium. Part 2 focuses on applications of computational complexity theory to game theory and economics. |
| computer science and economics: Computational Economics David A. Kendrick, P. Ruben Mercado, Hans M. Amman, 2011-10-23 The ability to conceptualize an economic problem verbally, to formulate it as a mathematical model, and then represent the mathematics in software so that the model can be solved on a computer is a crucial skill for economists. Computational Economics contains well-known models--and some brand-new ones--designed to help students move from verbal to mathematical to computational representations in economic modeling. The authors' focus, however, is not just on solving the models, but also on developing the ability to modify them to reflect one's interest and point of view. The result is a book that enables students to be creative in developing models that are relevant to the economic problems of their times. Unlike other computational economics textbooks, this book is organized around economic topics, among them macroeconomics, microeconomics, and finance. The authors employ various software systems--including MATLAB, Mathematica, GAMS, the nonlinear programming solver in Excel, and the database systems in Access--to enable students to use the most advantageous system. The book progresses from relatively simple models to more complex ones, and includes appendices on the ins and outs of running each program. The book is intended for use by advanced undergraduates and professional economists and even, as a first exposure to computational economics, by graduate students. Organized by economic topics Progresses from simple to more complex models Includes instructions on numerous software systems Encourages customization and creativity |
| computer science and economics: Economics and Computation Jörg Rothe, 2024 This textbook connects three vibrant areas at the interface between economics and computer science: algorithmic game theory, computational social choice, and fair division. It thus offers an interdisciplinary treatment of collective decision making from an economic and computational perspective. Part I introduces to algorithmic game theory, focusing on both noncooperative and cooperative game theory. Part II introduces to computational social choice, focusing on both preference aggregation (voting) and judgment aggregation. Part III introduces to fair division, focusing on the division of both a single divisible resource (cake-cutting) and multiple indivisible and unshareable resources (multiagent resource allocation). In all these parts, much weight is given to the algorithmic and complexity-theoretic aspects of problems arising in these areas, and the interconnections between the three parts are of central interest. |
| computer science and economics: Quantum Computing Melanie Swan, Renato P. Dos Santos, Frank Witte, 2020 Quantum information and contemporary smart network domains are so large and complex as to be beyond the reach of current research approaches. Hence, new theories are needed for their understanding and control. Physics is implicated as smart networks are physical systems comprised of particle-many items interacting and reaching criticality and emergence across volumes of macroscopic and microscopic states. Methods are integrated from statistical physics, information theory, and computer science. Statistical neural field theory and the AdS/CFT correspondence are employed to derive a smart network field theory (SNFT) and a smart network quantum field theory (SNQFT) for the orchestration of smart network systems. Specifically, a smart network field theory (conventional or quantum) is a field theory for the organization of particle-many systems from a characterization, control, criticality, and novelty emergence perspective. This book provides insight as to how quantum information science as a paradigm shift in computing may influence other high-impact digital transformation technologies, such as blockchain and machine learning. Smart networks refer to the idea that the internet is no longer simply a communications network, but rather a computing platform. The trajectory is that of communications networks becoming computing networks (with self-executing code), and perhaps ultimately quantum computing networks. Smart network technologies are conceived as autonomous self-operating computing networks. This includes blockchain economies, deep learning neural networks, autonomous supply chains, self-piloting driving fleets, unmanned aerial vehicles, industrial robotics cloudminds, real-time bidding for advertising, high-frequency trading networks, smart city IoT sensors, and the quantum internet. |
| computer science and economics: Economics of Information Security and Privacy III Bruce Schneier, 2012-09-26 The Workshop on the Economics of Information Security (WEIS) is the leading forum for interdisciplinary scholarship on information security, combining expertise from the fields of economics, social science, business, law, policy and computer science. Prior workshops have explored the role of incentives between attackers and defenders, identified market failures dogging Internet security, and assessed investments in cyber-defense. Current contributions build on past efforts using empirical and analytic tools to not only understand threats, but also strengthen security through novel evaluations of available solutions. Economics of Information Security and Privacy III addresses the following questions: how should information risk be modeled given the constraints of rare incidence and high interdependence; how do individuals' and organizations' perceptions of privacy and security color their decision making; how can we move towards a more secure information infrastructure and code base while accounting for the incentives of stakeholders? |
| computer science and economics: Computational Economics Oscar Afonso, Paulo B. Vasconcelos, 2015-08-27 Computational Economics: A concise introduction is a comprehensive textbook designed to help students move from the traditional and comparative static analysis of economic models, to a modern and dynamic computational study. The ability to equate an economic problem, to formulate it into a mathematical model and to solve it computationally is becoming a crucial and distinctive competence for most economists. This vital textbook is organized around static and dynamic models, covering both macro and microeconomic topics, exploring the numerical techniques required to solve those models. A key aim of the book is to enable students to develop the ability to modify the models themselves so that, using the MATLAB/Octave codes provided on the book and on the website, students can demonstrate a complete understanding of computational methods. This textbook is innovative, easy to read and highly focused, providing students of economics with the skills needed to understand the essentials of using numerical methods to solve economic problems. It also provides more technical readers with an easy way to cope with economics through modelling and simulation. Later in the book, more elaborate economic models and advanced numerical methods are introduced which will prove valuable to those in more advanced study. This book is ideal for all students of economics, mathematics, computer science and engineering taking classes on Computational or Numerical Economics. |
| computer science and economics: The Economics of Computers William F. Sharpe, 1969 |
| computer science and economics: Data Science for Economics and Finance Sergio Consoli, Diego Reforgiato Recupero, Michaela Saisana, 2021 This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications. |
| computer science and economics: Foundations of Mathematical Economics Michael Carter, 2001-10-26 This book provides a comprehensive introduction to the mathematical foundations of economics, from basic set theory to fixed point theorems and constrained optimization. Rather than simply offer a collection of problem-solving techniques, the book emphasizes the unifying mathematical principles that underlie economics. Features include an extended presentation of separation theorems and their applications, an account of constraint qualification in constrained optimization, and an introduction to monotone comparative statics. These topics are developed by way of more than 800 exercises. The book is designed to be used as a graduate text, a resource for self-study, and a reference for the professional economist. |
| computer science and economics: The Science of Economics Raymond Makewell, 2013-06-01 Based on a three-year course prepared by Leon MacLaren for the School of Economic Science in London in the late 1960s, this book reassesses the first principles of economics. Leon MacLaren (1910–1994) was a barrister, politician, philosopher, and the founder of the School of Economic Science. In his view, science is a study of laws that exist in nature, while economics is a study of the humanities with the interaction between human nature and the natural universe at its heart. With original subject matter from his economic course and introducing more recent examples and statistics from Australia, Canada, New Zealand, the UK, and the United States, the study examines the major characteristics of the modern economy—such as banking, taxation, and international trade—and considers the role of the government in economic affairs. It concludes with an examination of society's structure as a whole, the part economic activity plays in the bigger picture, and the social and cultural influences that shape the production and distribution of wealth. |
| computer science and economics: Artificial Economics Ruben Mercado, 2021-11-04 An introductory overview of the methods, models and interdisciplinary links of artificial economics. Addresses the differences between the assumptions and methods of artificial economics and those of mainstream economics. This is one of the first books to fully address, in an intuitive and conceptual form, this new way of doing economics. |
| computer science and economics: Twenty Lectures on Algorithmic Game Theory Tim Roughgarden, 2016-08-30 Computer science and economics have engaged in a lively interaction over the past fifteen years, resulting in the new field of algorithmic game theory. Many problems that are central to modern computer science, ranging from resource allocation in large networks to online advertising, involve interactions between multiple self-interested parties. Economics and game theory offer a host of useful models and definitions to reason about such problems. The flow of ideas also travels in the other direction, and concepts from computer science are increasingly important in economics. This book grew out of the author's Stanford University course on algorithmic game theory, and aims to give students and other newcomers a quick and accessible introduction to many of the most important concepts in the field. The book also includes case studies on online advertising, wireless spectrum auctions, kidney exchange, and network management. |
| computer science and economics: Computer Science Subrata Dasgupta, 2016 While the development of Information Technology has been obvious to all, the underpinning computer science has been less apparent. Subrata Dasgupta provides a thought-provoking introduction to the field and its core principles, considering computer science as a science of symbol processing. |
| computer science and economics: Software Engineering Economics Barry W. Boehm, 1981 Software Engineering Economics is an invaluable guide to determining software costs, applying the fundamental concepts of microeconomics to software engineering, and utilizing economic analysis in software engineering decision making. |
| computer science and economics: Science in the Age of Computer Simulation Eric Winsberg, 2010-10-30 Digital computer simulation helps study phenomena of great complexity, but how much do we know about the limits and possibilities of this new scientific practice? How do simulations compare to traditional experiments? And are they reliable? Scrutinizing these issues with a philosophical lens, Eric Winsberg explores the impact of simulation on such issues as the nature of scientific evidence, the role of values in science, the nature and role of fictions in science, and the relationship between simulation and experiment, theories and data, and theories at different levels of description--Cover. |
| computer science and economics: Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry Chkoniya, Valentina, 2021-06-25 The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students. |
| computer science and economics: Differential Equations and Numerical Analysis Valarmathi Sigamani, John J. H. Miller, Ramanujam Narasimhan, Paramasivam Mathiazhagan, Franklin Victor, 2016-08-18 This book offers an ideal introduction to singular perturbation problems, and a valuable guide for researchers in the field of differential equations. It also includes chapters on new contributions to both fields: differential equations and singular perturbation problems. Written by experts who are active researchers in the related fields, the book serves as a comprehensive source of information on the underlying ideas in the construction of numerical methods to address different classes of problems with solutions of different behaviors, which will ultimately help researchers to design and assess numerical methods for solving new problems. All the chapters presented in the volume are complemented by illustrations in the form of tables and graphs. |
| computer science and economics: Linear Programming and Economic Analysis Robert Dorfman, Paul A. Samuelson, Robert M. Solow, 2012-10-10 Designed primarily for economists and those interested in management economics who are not necessarily accomplished mathematicians, this text offers a clear, concise exposition of the relationship of linear programming to standard economic analysis. The research and writing were supported by The RAND Corporation in the late 1950s. Linear programming has been one of the most important postwar developments in economic theory, but until publication of the present volume, no text offered a comprehensive treatment of the many facets of the relationship of linear programming to traditional economic theory. This book was the first to provide a wide-ranging survey of such important aspects of the topic as the interrelations between the celebrated von Neumann theory of games and linear programming, and the relationship between game theory and the traditional economic theories of duopoly and bilateral monopoly. Modern economists will especially appreciate the treatment of the connection between linear programming and modern welfare economics and the insights that linear programming gives into the determinateness of Walrasian equilibrium. The book also offers an excellent introduction to the important Leontief theory of input-output as well as extensive treatment of the problems of dynamic linear programming. Successfully used for three decades in graduate economics courses, this book stresses practical problems and specifies important concrete applications. |
| computer science and economics: Economics of Information Security L. Jean Camp, Stephen Lewis, 2006-04-11 Designed for managers struggling to understand the risks in organizations dependent on secure networks, this book applies economics not to generate breakthroughs in theoretical economics, but rather breakthroughs in understanding the problems of security. |
| computer science and economics: The Fourth Industrial Revolution Klaus Schwab, 2017-01-03 World-renowned economist Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, explains that we have an opportunity to shape the fourth industrial revolution, which will fundamentally alter how we live and work. Schwab argues that this revolution is different in scale, scope and complexity from any that have come before. Characterized by a range of new technologies that are fusing the physical, digital and biological worlds, the developments are affecting all disciplines, economies, industries and governments, and even challenging ideas about what it means to be human. Artificial intelligence is already all around us, from supercomputers, drones and virtual assistants to 3D printing, DNA sequencing, smart thermostats, wearable sensors and microchips smaller than a grain of sand. But this is just the beginning: nanomaterials 200 times stronger than steel and a million times thinner than a strand of hair and the first transplant of a 3D printed liver are already in development. Imagine “smart factories” in which global systems of manufacturing are coordinated virtually, or implantable mobile phones made of biosynthetic materials. The fourth industrial revolution, says Schwab, is more significant, and its ramifications more profound, than in any prior period of human history. He outlines the key technologies driving this revolution and discusses the major impacts expected on government, business, civil society and individuals. Schwab also offers bold ideas on how to harness these changes and shape a better future—one in which technology empowers people rather than replaces them; progress serves society rather than disrupts it; and in which innovators respect moral and ethical boundaries rather than cross them. We all have the opportunity to contribute to developing new frameworks that advance progress. |
| computer science and economics: Advances in Intelligent Systems, Computer Science and Digital Economics IV Zhengbing Hu, Yong Wang, Matthew He, 2023-01-28 This book comprises high-quality peer-reviewed research papers presented at the 4th International Symposium on Computer Science, Digital Economy and Intelligent Systems (CSDEIS2022), held in Wuhan, China, from November 11–13, 2022, organized jointly by the Wuhan University of Technology, Hubei University of Technology, Wuhan University of Science and Technology, the Polish Operational and Systems Society, and the International Center of Informatics and Computer Science (ICICS). The topics discussed in the book include state-of-the-art papers in computer science and their technological applications; intelligent systems and intellectual approaches; digital economics and educational approaches. It is an excellent source of references for researchers, graduate students, engineers, management practitioners, and undergraduate students interested in computer science and its applications in engineering and management. |
| computer science and economics: Mathematical Methods and Theory in Games, Programming, and Economics Samuel Karlin, 1959 V. 1 : Matrix games, programming, and mathematical economics. v. 2 : The theory of infinite games. |
| computer science and economics: Creating the Market University Elizabeth Popp Berman, 2012-01-08 Academic science in the U.S. once self-consciously avoided the market. But today it is seen as an economic engine that keeps the nation globally competitive. Creating the Market University compares the origins of biotech entrepreneurship, university patenting, and university-industry research centers to show how government decisions shaped by a new argument--that innovation drives the economy-transformed academic science-- Provided by publisher. |
| computer science and economics: Social and Economic Networks Matthew O. Jackson, 2010-11-01 Networks of relationships help determine the careers that people choose, the jobs they obtain, the products they buy, and how they vote. The many aspects of our lives that are governed by social networks make it critical to understand how they impact behavior, which network structures are likely to emerge in a society, and why we organize ourselves as we do. In Social and Economic Networks, Matthew Jackson offers a comprehensive introduction to social and economic networks, drawing on the latest findings in economics, sociology, computer science, physics, and mathematics. He provides empirical background on networks and the regularities that they exhibit, and discusses random graph-based models and strategic models of network formation. He helps readers to understand behavior in networked societies, with a detailed analysis of learning and diffusion in networks, decision making by individuals who are influenced by their social neighbors, game theory and markets on networks, and a host of related subjects. Jackson also describes the varied statistical and modeling techniques used to analyze social networks. Each chapter includes exercises to aid students in their analysis of how networks function. This book is an indispensable resource for students and researchers in economics, mathematics, physics, sociology, and business. |
| computer science and economics: Advances in Intelligent Systems, Computer Science and Digital Economics III Zhengbing Hu, Sergei Gavriushin, Sergey Petoukhov, Matthew He, 2022-03-10 The book comprises high-quality refereed research papers presented at the Third International Symposium on Computer Science, Digital Economy, and Intelligent Systems (CSDEIS2021), held in Moscow, Russia, on December 25-26, 2021, organized jointly by the Mechanical Engineering Research Institute of the Russian Academy of Sciences,Moscow State Technical University, and the International Research Association of Modern Education and Computer Science. The topics discussed in the book includes state-of-the-art papers in computer science and their technological applications; intelligent systems and intellectual approaches; digital economics and methodological approaches. It is an excellent source of references for researchers, graduate students, engineers, management practitioners, and undergraduate students interested in computer science and its applications in engineering and management. |
| computer science and economics: Economics of Grids, Clouds, Systems, and Services Konstantinos Tserpes, Jörn Altmann, José Ángel Bañares, Orna Agmon Ben-Yehuda, Karim Djemame, Vlado Stankovski, Bruno Tuffin, 2021 Chapters AI Technologies and Motives for AI Adoption by Countries and Firms: A Systematic Literature Review; Knowledge Management Framework for Cloud Federation; Architecture for Orchestrating Containers in Cloud and Towards Software Compliance Specification and Enforcement using TOSCA are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. |
| computer science and economics: Selfish Routing and the Price of Anarchy Tim Roughgarden, 2005-05-06 An analysis of the loss in performance caused by selfish, uncoordinated behavior in networks. Most of us prefer to commute by the shortest route available, without taking into account the traffic congestion that we cause for others. Many networks, including computer networks, suffer from some type of this selfish routing. In Selfish Routing and the Price of Anarchy, Tim Roughgarden studies the loss of social welfare caused by selfish, uncoordinated behavior in networks. He quantifies the price of anarchy—the worst-possible loss of social welfare from selfish routing—and also discusses several methods for improving the price of anarchy with centralized control. Roughgarden begins with a relatively nontechnical introduction to selfish routing, describing two important examples that motivate the problems that follow. The first, Pigou's Example, demonstrates that selfish behavior need not generate a socially optimal outcome. The second, the counterintiuitve Braess's Paradox, shows that network improvements can degrade network performance. He then develops techniques for quantifying the price of anarchy (with Pigou's Example playing a central role). Next, he analyzes Braess's Paradox and the computational complexity of detecting it algorithmically, and he describes Stackelberg routing, which improves the price of anarchy using a modest degree of central control. Finally, he defines several open problems that may inspire further research. Roughgarden's work will be of interest not only to researchers and graduate students in theoretical computer science and optimization but also to other computer scientists, as well as to economists, electrical engineers, and mathematicians. |
| computer science and economics: Thinking Like an Economist Elizabeth Popp Berman, 2023-08-08 The story of how economic reasoning came to dominate Washington between the 1960s and 1980s—and why it continues to constrain progressive ambitions today For decades, Democratic politicians have frustrated progressives by tinkering around the margins of policy while shying away from truly ambitious change. What happened to bold political vision on the left, and what shrunk the very horizons of possibility? In Thinking like an Economist, Elizabeth Popp Berman tells the story of how a distinctive way of thinking—an “economic style of reasoning”—became dominant in Washington between the 1960s and the 1980s and how it continues to dramatically narrow debates over public policy today. Introduced by liberal technocrats who hoped to improve government, this way of thinking was grounded in economics but also transformed law and policy. At its core was an economic understanding of efficiency, and its advocates often found themselves allied with Republicans and in conflict with liberal Democrats who argued for rights, equality, and limits on corporate power. By the Carter administration, economic reasoning had spread throughout government policy and laws affecting poverty, healthcare, antitrust, transportation, and the environment. Fearing waste and overspending, liberals reined in their ambitions for decades to come, even as Reagan and his Republican successors argued for economic efficiency only when it helped their own goals. A compelling account that illuminates what brought American politics to its current state, Thinking like an Economist also offers critical lessons for the future. With the political left resurgent today, Democrats seem poised to break with the past—but doing so will require abandoning the shibboleth of economic efficiency and successfully advocating new ways of thinking about policy. |
| computer science and economics: Combinatorial Auctions Peter C. Cramton, Yoav Shoham, Richard Steinberg, 2006 A synthesis of theoretical and practical research on combinatorial auctions from the perspectives of economics, operations research, and computer science. |
| computer science and economics: Introduction to Economic Analysis R. Preston McAfee, 2009-09-24 This book presents introductory economics material using standard mathematical tools, including calculus. It is designed for a relatively sophisticated undergraduate who has not taken a basic university course in economics. The book can easily serve as an intermediate microeconomics text. The focus of this book is on the conceptual tools. Contents: 1) What is Economics? 2) Supply and Demand. 3) The US Economy. 4) Producer Theory. 5) Consumer Theory. 6) Market Imperfections. 7) Strategic Behavior. |
| computer science and economics: Analytical Political Economy Roberto Veneziani, Luca Zamparelli, 2018-06-11 Offering a unique picture of recent developments in a range of non-conventional theoretical approaches in economics, this book introduces readers to the study of Analytical Political Economy and the changes within the subject. Includes a wide range of topics and theoretical approaches that are critically and thoroughly reviewed Contributions within the book are written according to the highest standards of rigor and clarity that characterize academic work Provides comprehensive and well-organized surveys of cutting-edge empirical and theoretical work covering an exceptionally wide range of areas and fields Topics include macroeconomic theories of growth and distribution; agent-based and stock-flow consistent models; financialization and Marxian price and value theory Investigates exploitation theory; trade theory; the role of expectations and ‘animal spirits’ on macroeconomic performance as well as empirical research in Marxian economics |
| computer science and economics: Coping with Complexity H W Gottinger, 1983-09-30 |
| computer science and economics: Cogs and Monsters Diane Coyle, 2021-10-12 How economics needs to change to keep pace with the twenty-first century and the digital economy Digital technology, big data, big tech, machine learning, and AI are revolutionizing both the tools of economics and the phenomena it seeks to measure, understand, and shape. In Cogs and Monsters, Diane Coyle explores the enormous problems—but also opportunities—facing economics today and examines what it must do to help policymakers solve the world’s crises, from pandemic recovery and inequality to slow growth and the climate emergency. Mainstream economics, Coyle says, still assumes people are “cogs”—self-interested, calculating, independent agents interacting in defined contexts. But the digital economy is much more characterized by “monsters”—untethered, snowballing, and socially influenced unknowns. What is worse, by treating people as cogs, economics is creating its own monsters, leaving itself without the tools to understand the new problems it faces. In response, Coyle asks whether economic individualism is still valid in the digital economy, whether we need to measure growth and progress in new ways, and whether economics can ever be objective, since it influences what it analyzes. Just as important, the discipline needs to correct its striking lack of diversity and inclusion if it is to be able to offer new solutions to new problems. Filled with original insights, Cogs and Monsters offers a road map for how economics can adapt to the rewiring of society, including by digital technologies, and realize its potential to play a hugely positive role in the twenty-first century. |
Computer - Wikipedia
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Computer | Definition, History, Operating Systems, & Facts | Britannica
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Computer - Wikipedia
A computer is a machine that can be programmed to automatically carry out sequences of arithmetic or logical …
Computer | Definition, History, Operating Systems, & Facts
A computer is a programmable device for processing, storing, and displaying information. Learn more in this …
What is a Computer?
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