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The Football Association of England has become a multi-billion pound industry. But how did English football become not only the defining sport of the nation but also one of the most successful sports in the world? With The Leaguers, football historian Matthew Taylor tells the story of the early days of professional football in England, revealing the distant origins of today's game. Making extensive use of archival materials from football clubs, unions, and associations, Taylor presents a compelling picture of football teams and players in the early days of the twentieth century, tracing the development of the system of professional teams from the hundreds of town, club, and school teams that dotted the countryside. The top tier of those teams comprised the Football League that, by the 1920s, was synonymous with the very idea of professional football in the minds of fans and sportswriters alike. The Leaguers illuminates the role played by the Football League-and by successful clubs in the League such as Arsenal and Aston Villa'as the rules, standards, and structure of the modern game were being codified. Taylor also considers the careers and influences of early players, including such well-known names as Billy Meredith, "Dixie" Dean, and Alex James. As football's popularity grew and sports media proliferated, players found themselves becoming national stars, their portraits on cigarette cards bought by fans throughout England. The first full-length history of the early days of the Football League, The Leaguers will be essential reading for football fans who want to know how their favorite sport grew from modest origins to the worldwide phenomenon that is English football today.

Soccer --- Association football --- English football --- European football --- Football (Soccer) --- Football --- History. --- Football League --- English Football League

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COVID-induced work from home, demand for government support, changing attitudes toward paternity leave, climate change and advances in AI: these and other factors have profoundly changed our relationship to work.Work is so integral to our lives and our culture that we have internalized beliefs about its value and have built our economies and lifestyles around those beliefs. Expert Matthew Taylor reviews how the meaning, status, and structure of work have changed across history and societies. He goes on to posit that we are approaching a new era of work. He outlines some of the factors that might lead to change, including the adoption of forms of universal basic income, the growth of the zero- or low-cost economy (renewable energy, user-generated content, community mutual support), and the growth of self-employment and quasi- autonomous ways of working (including from home) in organizations. He concludes that such changes might foster a more fundamental shift: a growing intolerance of the idea of work as a burden and a desire to transform it from something imposed on us into simply the means by which we live our best lives together, recreating in modern conditions with modern resources a prehistoric unity between being and working.

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In reinforcement learning (RL) problems, learning agents sequentially execute actions with the goal of maximizing a reward signal. The RL framework has gained popularity with the development of algorithms capable of mastering increasingly complex problems, but learning difficult tasks is often slow or infeasible when RL agents begin with no prior knowledge. The key insight behind "transfer learning" is that generalization may occur not only within tasks, but also across tasks. While transfer has been studied in the psychological literature for many years, the RL community has only recently begun to investigate the benefits of transferring knowledge. This book provides an introduction to the RL transfer problem and discusses methods which demonstrate the promise of this exciting area of research. The key contributions of this book are: Definition of the transfer problem in RL domains Background on RL, sufficient to allow a wide audience to understand discussed transfer concepts Taxonomy for transfer methods in RL Survey of existing approaches In-depth presentation of selected transfer methods Discussion of key open questions By way of the research presented in this book, the author has established himself as the pre-eminent worldwide expert on transfer learning in sequential decision making tasks. A particular strength of the research is its very thorough and methodical empirical evaluation, which Matthew presents, motivates, and analyzes clearly in prose throughout the book. Whether this is your initial introduction to the concept of transfer learning, or whether you are a practitioner in the field looking for nuanced details, I trust that you will find this book to be an enjoyable and enlightening read. Peter Stone, Associate Professor of Computer Science.

Computer Science --- Engineering & Applied Sciences --- Cybernetics. --- Reinforcement learning. --- Mechanical brains --- Engineering. --- Artificial intelligence. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Machine learning --- Reinforcement (Psychology) --- Learning classifier systems --- Control theory --- Electronics --- System theory --- Artificial Intelligence.

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This book constitutes the refereed proceedings of the Second International Conference on Distributed Artificial Intelligence, DAI 2020, held in Nanjing, China, in October 2020. The 9 full papers presented in this book were carefully reviewed and selected from 22 submissions. DAI aims at bringing together international researchers and practitioners in related areas including general AI, multiagent systems, distributed learning, computational game theory, etc., to provide a single, high-profile, internationally renowned forum for research in the theory and practice of distributed AI. Due to the Corona pandemic this event was held virtually.

Artificial intelligence. --- Special purpose computers. --- Application software. --- Computers. --- Computer communication systems. --- Mathematical statistics. --- Artificial Intelligence. --- Special Purpose and Application-Based Systems. --- Computer Applications. --- Computing Milieux. --- Computer Communication Networks. --- Probability and Statistics in Computer Science. --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Electronic data processing --- Network computers --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Special purpose computers --- Computers --- AI (Artificial intelligence) --- Artificial thinking --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Statistical methods --- Distributed processing --- Distributed artificial intelligence

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Brazil features regularly in global comparisons of large developing economies. Yet since the 1980s, the country has been caught in a low-level equilibrium, marked by lackluster growth and destructive inequality. One cause is the country's enduring commitment to a set of ideas and institutions labelled developmentalism. This book argues that developmentalism has endured, despite hyperactive reform, because institutional complementarities across economic and political spheres sustain and drive key actors and strategies that are individually advantageous, but collectively suboptimal. Although there has been incremental evolution in some institutions, complementarities across institutions sustain a pattern of 'decadent developmentalism' that swamps systemic change. Breaking new ground, Taylor shows how macroeconomic and microeconomic institutions are tightly interwoven with patterns of executive-legislative relations, bureaucratic autonomy, and oversight. His analysis of institutional complementarities across these five dimensions is relevant not only to Brazil but also to the broader study of comparative political economy.

Economic development --- Democracy --- Development, Economic --- Economic growth --- Growth, Economic --- Economic policy --- Economics --- Statics and dynamics (Social sciences) --- Development economics --- Resource curse --- Brazil --- Politics and government