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

Amazon.com Price:  $44.46 (as of 22/04/2019 22:29 PST- Details)

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Description

An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance.

Many important problems involve decision making under uncertainty — that is, choosing actions based on frequently imperfect observations, with unknown outcomes. Designers of automated decision give a boost to systems should take into account the more than a few sources of uncertainty at the same time as 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 in the back of 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 the use of consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It may be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It’s going to also be a valuable professional reference for researchers in a number of disciplines.

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