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  1. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.Judea Pearl - 1988 - Morgan Kaufmann.
    The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
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  • Symbolic logic and mechanical theorem proving.Chin-Liang Chang - 1973 - San Diego: Academic Press. Edited by Richard Char-Tung Lee.
    This book contains an introduction to symbolic logic and a thorough discussion of mechanical theorem proving and its applications. The book consists of three major parts. Chapters 2 and 3 constitute an introduction to symbolic logic. Chapters 4–9 introduce several techniques in mechanical theorem proving, and Chapters 10 an 11 show how theorem proving can be applied to various areas such as question answering, problem solving, program analysis, and program synthesis.
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  • An Introduction to Default Logic.Philippe Besnard - 2010 - Springer.
    This book is written for those who are interested in a fonnalization of human reasoning, especially in order to build "intelligent" computer systems. Thus, it is mainly designed for the Artificial Intelligence community, both students and researchers, although it can be useful for people working in related fields like cognitive psychology. The major theme is not Artificial Intelligence applications, although these are discussed throughout in sketch fonn. Rather, the book places a heavy emphasis on the fonnal development of default logic, (...)
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  • Reasoning with Incomplete Information.David W. Etherington - 1988 - Pitman Publishing.
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