Decision Making Under Uncertainty: Theory and Application (MIT Lincoln Laboratory Series)

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9780262029254: Decision Making Under Uncertainty: Theory and Application (MIT Lincoln Laboratory Series)
From the Publisher:

Many important problems involve decision making under uncertainty--that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.

About the Author:

Mykel J. Kochenderfer is Assistant Professor in the Department of Aeronautics and Astronautics at Stanford University. He is a consultant for the MIT Lincoln Laboratory.

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Kochenderfer, Mykel J.
ISBN 10: 0262029251 ISBN 13: 9780262029254
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Kochenderfer, Mykel J.
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Descripción MIT Press Ltd, United States, 2015. Hardback. Estado de conservación: New. 231 x 180 mm. Language: English . Brand New Book. Many important problems involve decision making under uncertainty -- that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines. Nº de ref. de la librería AAZ9780262029254

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Kochenderfer, Mykel J.
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Descripción MIT Press 2015-08-07, 2015. Estado de conservación: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely. Nº de ref. de la librería NU-GRD-05267953

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Kochenderfer, Mykel J.
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Descripción MIT Press Ltd, United States, 2015. Hardback. Estado de conservación: New. 231 x 180 mm. Language: English . Brand New Book. Many important problems involve decision making under uncertainty -- that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines. Nº de ref. de la librería AAZ9780262029254

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Kochenderfer, Mykel J.
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Descripción MIT Press, 2015. HRD. Estado de conservación: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Nº de ref. de la librería GB-9780262029254

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Descripción MIT Press Ltd 2015-08-11, Cambridge, Mass., 2015. hardback. Estado de conservación: New. Nº de ref. de la librería 9780262029254

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Descripción The MIT Press, 2015. Estado de conservación: New. Series: MIT Lincoln Laboratory Series. Num Pages: 352 pages, 19 color illus., 72 b&w illus. BIC Classification: PBW; TJFM; UYQM. Category: (G) General (US: Trade). Dimension: 185 x 235 x 28. Weight in Grams: 824. . 2015. 1st Edition. Hardcover. . . . . . Nº de ref. de la librería V9780262029254

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Descripción 2015. Hardback. Estado de conservación: NEW. 9780262029254 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Nº de ref. de la librería HTANDREE01143807

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