Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (Morgan Kaufmann Series in Representation and Reasoning)
$56.50
Description
Book Synopsis: Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information.
Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
Details
Unlock the power of intelligent systems with Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Delve into the world of uncertainty and partial belief with this comprehensive guide that provides a solid foundation in probabilistic reasoning. Discover how belief networks can revolutionize your approach to decision-making and drive meaningful insights from incomplete information.
Gain a competitive edge in AI, decision theory, and cognitive psychology with the cutting-edge concepts presented in this book. From diagnosis to planning, speech recognition to multi-sensor fusion, the applications of probabilistic reasoning are limitless. Elevate your understanding of intelligent systems and embark on a journey to unleash their full potential.
Go beyond traditional AI approaches and embrace a new paradigm of reasoning with Probabilistic Reasoning in Intelligent Systems. Explore the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic as you embark on a transformative learning experience. Equip yourself with practical tools and methodologies that can be implemented across various disciplines with immediate impact.
Ready to revolutionize your approach to uncertainty and decision-making? Take the first step towards mastering probabilistic reasoning with Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Uncover the secrets of belief networks, modular inputs, and parallel computation that will redefine the way you tackle complex problems. Elevate your knowledge and expertise in AI, operations research, and beyond with this essential resource.
Embark on a journey of discovery and innovation with Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Elevate your understanding of intelligent systems and unlock new possibilities in decision-making and reasoning. Order your copy today and take the first step towards mastering the art of probabilistic reasoning.
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