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.
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.
The book aims to integrate our understanding of mammalian societies into a novel synthesis that is relevant to behavioural ecologists, ecologists, and anthropologists. It adopts a coherent structure that deals initially with the characteristics and strategies of females, before covering those of males, cooperative societies and hominid societies. It reviews our current understanding both of the structure of societies and of the strategies of individuals; it combines coverage of relevant areas of theory with coverage of interspecific comparisons, intraspecific comparisons and experiments; it explores both evolutionary causes of different traits and their ecological consequences; and it integrates research on different groups of mammals with research on primates and humans and attempts to put research on human societies into a broader perspective.
Bestselling author and staff writer for "The New Yorker" Groopman edits this year's volume of the finest science and nature writing. Contributors include Walter Kirn, Ron Rosenbaum, Jeffrey Toobin, and Oliver Sacks.
A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them. The book first addresses the problem of reasoning about uncertainty and objectives in simple decisions at a single point in time, and then turns to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain. It goes on to address model uncertainty, when we do not start with a known model and must learn how to act through interaction with the environment; state uncertainty, in which we do not know the current state of the environment due to imperfect perceptual information; and decision contexts involving multiple agents. The book focuses primarily on planning and reinforcement learning, although some of the techniques presented draw on elements of supervised learning and optimization. Algorithms are implemented in the Julia programming language. Figures, examples, and exercises convey the intuition behind the various approaches presented.
The vast scope of conservation problems has forced biologists and managers to rely on "surrogate" species to serve as shortcuts to guide their decision making. These species-known by a host of different terms, including indicator, umbrella, and flagship species-act as proxies to represent larger conservation issues, such as the location of biodiversity hotspots or general ecosystem health. Synthesizing an immense body of literature, conservation biologist and field researcher Tim Caro offers systematic definitions of surrogate species concepts, explores biological theories that underlie them, considers how surrogate species are chosen, critically examines evidence for and against their utility, and makes recommendations for their continued use. The book clarifies terminology and contrasts how different terms are used in the real world considers the ecological, taxonomic, and political underpinnings of these shortcuts identifies criteria that make for good surrogate species outlines the circumstances where the application of the surrogate species concept shows promise Conservation by Proxy is a benchmark reference that provides clear definitions and common understanding of the evidence and theory behind surrogate species. It is the first book to review and bring together literature on more than fifteen types of surrogate species, enabling us to assess their role in conservation and offering guidelines on how they can be used most effectively.
Describes new ways of looking at environmental science and politics, and discusses the problems of formulating and implementing environmental policy, particularly in the global arena and in developing countries.
The uplands are a crucial source of ecosystem services, such as water provision, carbon retention, maintenance of biodiversity, provision of recreation value and cultural heritage. This puts them in the focus of both environmental and social scientists as well as practitioners and land managers.. This volume brings together a wealth of knowledge of the British uplands from diverse but interrelated fields of study, clearly demonstrating their importance in 21st Century Britain, and indicating how we may through interdisciplinary approaches meet the challenges provided by past and future drivers of environmental change. The upland environments are subject to change. They face imminent threats as well as opportunities from pressures such as climate change, changes in land management and related changes in fire risk, increases in erosion and water colour, degradation of habitats, altered wildlife and recreational value, as well as significant changes in the economy of these marginal areas. This book presents up-to-date scientific background information, addresses policy related issues and lays out pressing land management questions. A number of world-class experts provide a review of cutting-edge natural and social science and an assessment of past, current and potential future management strategies, policies and other drivers of change. After appraisal of key concepts and principles, chapters provide specific examples and applications by focussing on UK upland areas and specifically the Peak District National Park as a key example for other highly valuable upland regions.
Issues of scale have become increasingly important to ecologists. This book addresses the structure of regional (large-scale) ecological assemblages or communities, and the influence this has at a local (small-scale) level. This macroecological perspective is essential for the broader study of ecology because the structure and function of local communities cannot be properly understood without reference to the region in which they are situated. The book reviews and synthesizes the issues of current importance in macroecology, providing a balanced summary of the field that will be useful for biologists at advanced undergraduate level and above. These general issues are illustrated by frequent reference to specific well-studied local and regional assemblages -- an approach that serves to relate the macroecological perspective (which is perhaps often difficult to comprehend) to the everyday experience of local sites. Macroecology is an expanding and dynamic discipline. The broad aim of the book is to promote an understanding of why it is such an important part of the wider program of research into ecology. Summarises the current macroecological literature. Provides numerous examples of key patterns. Explicitly links local and regional scale processes. Exploits detailed knowledge of one species assemblage to explore broad issues in the structuring of biodiversity.
All organizations are political environments. Politics is present in all the major processes, including resource allocation, succession planning and equal opportunities. Yet being political is often regarded as a negative trait, associated with lack of authenticity, unethical behaviour and sociopathy. For employees, managing politics is a core skill. For coaches and mentors, there is the constant dilemma of how to help a client thrive in a political environment while retaining their authenticity. A critical distinction is between being politically aware or astute and being political or “playing politics”. This book aims to set out practical ways in which coaches and mentors can both maintain their own integrity and support their clients in doing the same, in politicised environments. It will draw on the experiences of coaches and mentors, leaders and managers in organisations around the world, and coach supervisors.
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.
Algorithms Illuminated is an accessible introduction to algorithms for anyone with at least a little programming experience, based on a sequence of popular online courses. Part 1 covers asymptotic analysis and big-O notation, divide-and-conquer algorithms, randomized algorithms, and several famous algorithms for sorting and selection.
This will help us customize your experience to showcase the most relevant content to your age group
Please select from below
Login
Not registered?
Sign up
Already registered?
Success – Your message will goes here
We'd love to hear from you!
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.