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With phenomenal profits at stake, the conflict would go all the way to the United States Supreme Court, in a case that involved not just the largest Wall Street banks but also the tech behemoths of Silicon Valley. The extraordinary story of Alice Corporation, a company created to reimagine financial markets, brings together an unlikely cast of characters: renowned author Kate Jennings, international banking insider Ian Shepherd, Enron CEO Jeffrey Skilling, German-born World War II historian Sigrid MacRae, J.P. Morgan deputy chair Roberto Mendoza - and his dog, Stanley. In the tradition of Michael Lewis's Flash Boys and The Big Short, Alice is a story of ground-breaking insights, legal intrigue and improbable friendships. Pinpointing the likely causes of the next financial crisis, Alice reveals the fight to build a safer, fairer financial future. Free Download Christine Lunardini, "Alice Paul: Equality for Women" English | 2012 | ISBN: 0813347610, 0367097737 | EPUB | pages: 218 | 0.3 mb Alice Paul: Equality for Women shows the dominant and unwavering role Paul played in the passage of the Nineteenth Amendment, granting the vote to American women. The dramatic details of Paul's imprisonment and solitary confinement, hunger strike, and force-feeding at the hands of the U.S. government illustrate her fierce devotion to the cause she spent her life promoting. Placed in the context of the first half of the twentieth century, Paul's story also touches on issues of progressivism and labor reform, race and class, World War I patriotism and America's emerging role as a global power, women's activism in the political sphere, and the global struggle for women's rights. 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The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging from problems in artificial intelligence to operations research or control engineering. In this book, we focus on those algorithms of reinforcement learning that build on the powerful theory of dynamic programming. We give a fairly comprehensive catalog of learning problems, describe the core ideas, note a large number of state of the art algorithms, followed by the discussion of their theoretical properties and limitations. Table of Contents: Markov Decision Processes / Value Prediction Problems / Control / For Further Exploration Free Download Sushil C. 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