Almost everyone is familiar with Monte Carlo's association with gambling, and its famous Casino. Many may also have come across the Monte Carlo fallacy, so-called after the Casino's roulette wheel ball fell on black 26th times in a row, costing players, who believed that the law of averages made such streaks impossible, millions of dollars. However, the Casino also lends its name to a tool of statistical forecasting, the Monte Carlo simulation, used to model the probability of uncertain outcomes that cannot be easily predicted from mathematical equations. This book provides a detailed account for how aspiring sports bettors can use a Monte Carlo simulation to improve the quality, and hopefully profitability, of their betting, and in doing so unravels the mystery of probability and variance that lies at the heart of all gambling.

Iceland truly lived the boom and bust. Once a tiny country on the edge of Europe, in less than two decades it became a global financial powerhouse. This is the story of how one man, one bank and one country experienced and affected the course of world economic history. Armann Thorvaldsson, a former CEO at Kaupthing in the UK, tells the story of how his company was transformed into a £6 billion international bank, by far the largest in his country’s history. Helping to build the biggest names in Icelandic business, Thorvaldsson represented the money behind such household names as easyJet, Matalan, Iceland and Karen Millen. As the boom got bigger, the Icelandic bankers worked and played hard with their international clients, including Gordon Ramsay, the Candy brothers, Mike Ashley and Robert Tchenguiz. Moving from Reykjavik to London, Monte Carlo and St Tropez, they seemed unstoppable. Yet, when the bust came, even the most frantic attempts to save the bank were fruitless, leading to the total collapse of the Icelandic economy. Thorvaldsson’s reflections on exactly what happened and why, make compelling reading.

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

How do we know if we can beat the bookmaker? That's easy: just look at our bank balance. But how do we know if we've not just been lucky? More specifically, how do we know that someone who says he can do it, and who is selling his 'expertise', can keep doing it again and again, through talent, skill and hard work? This book examines the techniques available to answer that question, to identify those qualities and to help the punter find value for money in an industry that appears to be largely built on trust and the influence of chance; to uncover the truth about sports tipsters and ultimately how to find the best tipsters - the 'Black Cats'.