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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 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.
These edited proceedings of the NATO Advanced Research Workshop detail the ongoing search for better ways of protecting human life, land, property and the environment by improved flood management. Such flood management is difficult enough in river basins controlled by a single authority, and becomes even more challenging when dealing with transboundary floods, which may originate in one country or jurisdiction and propagate downstream to another country, or jurisdiction.
MIL-HDBK-419A 29 DECEMBER 1987 Volume 2 of 2 Applications Unfortunately, few Military Handbooks address the need for defense against electromagnetic pulse (EMP) and cybersecurity. While EMP has been thought of as a remote possibility (who in his right mind is going to launch a nuclear weapon of any kind against the U.S.?) Advances in non-nuclear EMP, miniaturization of electronics and autonomous drones suddenly brings EMP into the role of the possible. No longer would an adversary need to risk retaliation when a drone from an unknown source attacks a vital facility. The information in this book is part of the solution to the question "How do we defend against EMP?" List of Applicable EMP and Cybersecurity Publications: MIL-STD-188-125-1 High-altitude electromagnetic pulse (HEMP) Protection For Ground-Based C4I Facilities Performing Critical, Time-Urgent Missions MIL-STD-188-124A Grounding, Bonding and Shielding for Common Long Haul/Tactical Communication Systems MIL-HDBK -1195 Radio Frequency Shielded Enclosures TOP 01-2-620 High-Altitude Electromagnetic Pulse (HEMP) Testing MIL-HDBK-1012/1 Electronic Facilities Engineering MIL-HDBK-1013/1A Design Guidelines for Physical Security of Facilities
There are many excellent books on quantum theory from which one can learn to compute energy levels, transition rates, cross sections, etc. The theoretical rules given in these books are routinely used by physicists to compute observable quantities. Their predictions can then be compared with experimental data. There is no fundamental disagreement among physicists on how to use the theory for these practical purposes. However, there are profound differences in their opinions on the ontological meaning of quantum theory. The purpose of this book is to clarify the conceptual meaning of quantum theory, and to explain some of the mathematical methods which it utilizes. This text is not concerned with specialized topics such as atomic structure, or strong or weak interactions, but with the very foundations of the theory. This is not, however, a book on the philosophy of science. The approach is pragmatic and strictly instrumentalist. This attitude will undoubtedly antagonize some readers, but it has its own logic: quantum phenomena do not occur in a Hilbert space, they occur in a laboratory.
For the experienced amateur astronomer who is wondering if there is something useful, valuable, and permanent that can be done with his or her observational skills, the answer is, “Yes, there is!” This is THE book for the amateur astronomer who is ready to take the next step in his or her astronomical journey. Till now there has been no text that points curious amateur astronomers to the research possibilities open to them. At the 2006 meeting of the Society for Astronomical Sciences, participants agreed that the lack of such a text was a serious gap in the astronomical book market. This book plugs that hole.
This book brings together a collection of invited interdisciplinary persp- tives on the recent topic of Object-based Image Analysis (OBIA). Its c- st tent is based on select papers from the 1 OBIA International Conference held in Salzburg in July 2006, and is enriched by several invited chapters. All submissions have passed through a blind peer-review process resulting in what we believe is a timely volume of the highest scientific, theoretical and technical standards. The concept of OBIA first gained widespread interest within the GIScience (Geographic Information Science) community circa 2000, with the advent of the first commercial software for what was then termed ‘obje- oriented image analysis’. However, it is widely agreed that OBIA builds on older segmentation, edge-detection and classification concepts that have been used in remote sensing image analysis for several decades. Nevert- less, its emergence has provided a new critical bridge to spatial concepts applied in multiscale landscape analysis, Geographic Information Systems (GIS) and the synergy between image-objects and their radiometric char- teristics and analyses in Earth Observation data (EO).