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From a bestselling historian, a daringly revisionist history of World War I The Pity of War makes a simple and provocative argument: the human atrocity known as the Great War was entirely England's fault. According to Niall Ferguson, England entered into war based on naive assumptions of German aims, thereby transforming a Continental conflict into a world war, which it then badly mishandled, necessitating American involvement. The war was not inevitable, Ferguson argues, but rather was the result of the mistaken decisions of individuals who would later claim to have been in the grip of huge impersonal forces. That the war was wicked, horrific, and inhuman is memorialized in part by the poetry of men like Wilfred Owen and Siegfried Sassoon, but also by cold statistics. Indeed, more British soldiers were killed in the first day of the Battle of the Somme than Americans in the Vietnam War. And yet, as Ferguson writes, while the war itself was a disastrous folly, the great majority of men who fought it did so with little reluctance and with some enthusiasm. For anyone wanting to understand why wars are fought, why men are willing to fight them and why the world is as it is today, there is no sharper or more stimulating guide than Niall Ferguson's The Pity of War.
This book revolutionized 19th-century American architecture and changed forever the type of building that was done in our country.
This is an overview of the current state of knowledge along with open problems and perspectives, clarified in such fields as non-standard inferences in description logics, logic of provability, logical dynamics and computability theory. The book includes contributions concerning the role of logic today, including unexpected aspects of contemporary logic and the application of logic. This book will be of interest to logicians and mathematicians in general.
Handbook of Knowledge Representation describes the essential foundations of Knowledge Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety of AI systems. This handbook is organized into three parts. Part I deals with general methods in Knowledge Representation and reasoning and covers such topics as classical logic in Knowledge Representation; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based problem solving; and Bayesian networks. Part II focuses on classes of knowledge and specialized representations, with chapters on temporal representation and reasoning; spatial and physical reasoning; reasoning about knowledge and belief; temporal action logics; and nonmonotonic causal logic. Part III discusses Knowledge Representation in applications such as question answering; the semantic web; automated planning; cognitive robotics; multi-agent systems; and knowledge engineering. This book is an essential resource for graduate students, researchers, and practitioners in knowledge representation and AI. * Make your computer smarter* Handle qualitative and uncertain information* Improve computational tractability to solve your problems easily