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12-year-old Kylan is a Viking slave; when he gets the chance to return to the Hebrides, the Lewis Chessmen he helped carve become his only hope of escape and survival.
THE 12 MILLION COPY BESTSELLING AUTHOR OF THE ENZO FILES AND THE CHINA THRILLERS AWARD WINNING AUTHOR OF THE CWA DAGGER IN THE LIBRARY 2021 'One of the best regarded crime series of recent years.' Independent 'No one can create a more eloquently written suspense novel than Peter May.' New York Journal of Books A MAN WITH NO NAME An unidentified corpse is recovered from a Lewis peat bog; the only clue to its identity being a DNA sibling match to a local farmer. A MAN WITH NO MEMORY But this islander, Tormod Macdonald - now an elderly man suffering from dementia - has always claimed to be an only child. A MAN WITH NO CHOICE When Tormod's family approach Fin Macleod for help, Fin feels duty-bound to solve the mystery. LOVED THE LEWIS MAN? Read book 3 in the Lewis trilogy, THE CHESSMEN LOVE PETER MAY? Buy his latest frontlist thriller, THE NIGHT GATE
This book provides comprehensive information and guidance for successfully staging a theatrical living chess game for children ages 9–14. It also prepares student to succeed in University Interscholastic League (UIL) Chess Puzzle. Living chess games have been referenced in works from classic authors such as Lewis Carroll and Kurt Vonnegut; this theater art was also mentioned in J.K. Rowling's Harry Potter and the Philosopher's Stone. With The Living Chess Game: Fine Arts Activities for Kids 9-14, any parent, librarian, teacher, or after-school instructor can successfully stage an educational and entertaining living chess game. This book will also help educators and librarians prepare students to succeed in University Interscholastic League (UIL) Chess Puzzle. The book's chess instruction enables children to perform, with understanding, as living chess pieces. The activities not only instruct students on how to research chess, but also teach a myriad of fine arts skills such as acting, composing music, choreographing movements, designing scenery, and scriptwriting, and the activities address content standards from the National Standards for Arts Education. The author has also provided a "resources and materials" section that explains the cultural reference of each activity's title and lists opportunities for parental involvement, such as tech support and attending students' performances.
Want to play chess like a champ? Dummies can help. From Netflix's “The Queen’s Gambit” to podcasts, virtual and mobile gaming, and beyond, chess is back in a big way. But, with all those kings, queens, and knights, chess can be a royal pain to grasp. Chess For Dummies is here to help beginners wrap their minds around the rules of the game, make sense of those puzzling pieces, and sharpen their chess strategy such that even Paul Morphy would be impressed. You’ll learn the laws of chess, its lingo, and engage in the art of the attack with the easy-to-follow, step-by-step explanations found in the latest edition of Chess For Dummies. Whether you’re playing chess online, in a tournament, or across the dining room table with a family member or friend, this hands-on guide is sure to capture your interest (and your opponent's queen), getting you up to speed on the game and its components and giving you the know-how you need to put the principles of play into action from the opening to the endgame. Grasp the rules of play and the nuances of each phase of the game Familiarize yourself with the pieces and the board Pick the perfect chess set and chessboard for you Get to know each of the pieces and their powers If you feel like you’re in a stalemate before you even begin a game, Chess For Dummies is your guide to forcing moves, raking bishops, and skewering your opponents like a true champion.
Action theory is the object of growing attention in a variety of scientific disciplines and this is the first volume to offer a synthetic view of the range of approaches possible in the topic. The volume focuses on the nexus of formal action theory with a startlingly diverse set of subjects, which range from logic, linguistics, artificial intelligence and automata theory to jurisprudence, deontology and economics. It covers semantic, mathematical and logical aspects of action, showing how the problem of action breaks the boundaries of traditional branches of logic located in syntactics and semantics and now lies on lies on the borderline between logical pragmatics and praxeology. The chapters here focus on specialized tasks in formal action theory, beginning with a thorough description and formalization of the language of action and moving through material on the differing models of action theory to focus on probabilistic models, the relations of formal action theory to deontic logic and its key applications in algorithmic and programming theory. The coverage thus fills a notable lacuna in the literary corpus and offers solid formal underpinning in cognitive science by approaching the problem of cognition as a composite action of mind.
An example-rich guide for beginners to start their reinforcement and deep reinforcement learning journey with state-of-the-art distinct algorithms Key FeaturesCovers a vast spectrum of basic-to-advanced RL algorithms with mathematical explanations of each algorithmLearn how to implement algorithms with code by following examples with line-by-line explanationsExplore the latest RL methodologies such as DDPG, PPO, and the use of expert demonstrationsBook Description With significant enhancements in the quality and quantity of algorithms in recent years, this second edition of Hands-On Reinforcement Learning with Python has been revamped into an example-rich guide to learning state-of-the-art reinforcement learning (RL) and deep RL algorithms with TensorFlow 2 and the OpenAI Gym toolkit. In addition to exploring RL basics and foundational concepts such as Bellman equation, Markov decision processes, and dynamic programming algorithms, this second edition dives deep into the full spectrum of value-based, policy-based, and actor-critic RL methods. It explores state-of-the-art algorithms such as DQN, TRPO, PPO and ACKTR, DDPG, TD3, and SAC in depth, demystifying the underlying math and demonstrating implementations through simple code examples. The book has several new chapters dedicated to new RL techniques, including distributional RL, imitation learning, inverse RL, and meta RL. You will learn to leverage stable baselines, an improvement of OpenAI’s baseline library, to effortlessly implement popular RL algorithms. The book concludes with an overview of promising approaches such as meta-learning and imagination augmented agents in research. By the end, you will become skilled in effectively employing RL and deep RL in your real-world projects. What you will learnUnderstand core RL concepts including the methodologies, math, and codeTrain an agent to solve Blackjack, FrozenLake, and many other problems using OpenAI GymTrain an agent to play Ms Pac-Man using a Deep Q NetworkLearn policy-based, value-based, and actor-critic methodsMaster the math behind DDPG, TD3, TRPO, PPO, and many othersExplore new avenues such as the distributional RL, meta RL, and inverse RLUse Stable Baselines to train an agent to walk and play Atari gamesWho this book is for If you’re a machine learning developer with little or no experience with neural networks interested in artificial intelligence and want to learn about reinforcement learning from scratch, this book is for you. Basic familiarity with linear algebra, calculus, and the Python programming language is required. Some experience with TensorFlow would be a plus.