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Uncertainty could be associated with wisdom, enterprise, and discovery. In ordinary speech, however, it has mostly negative connotations. There is "fear of the unknown" and "ignorance is bliss;" there are maxims to the effect that "what you don't know doesn't hurt you" (or: "bother you") in several languages. This volume suggests that we need be bothered by the excessive confidence with which scientists, particularly social scientists, present some of their conclusions and overstate their range of application. Otherwise many of the questions that should be raised about all the major uncertainties attending a particular issue routinely may continue to be thwarted or suppressed. Down playing uncertainty does not lead to more responsible or surer action, it sidetracks research agendas, and leaves the decision makers exposed to nasty surprise. This volume demonstrates that recognizing the many forms of uncertainty that enter into the development of any particular subject matter is a precondition for more responsible choice and deeper knowledge. Our purpose is to contribute to a broader appreciation of uncertainty than regularly accorded in any of the numerous disciplines represented here. The seventeenth-century French philosopher Descartes, quoted in this volume, wrote that "whoever is searching after truth must, once in his life, doubt all things; insofar as this is possible. " White areas left on maps of the world in past centuries were a much more productive challenge than marking the end of the known world with the pillars of Hercules.
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.
A call for a new form of democracy in which “hybrid forums” composed of experts and laypeople address such sociotechnical controversies as hazardous waste, genetically modified organisms, and nanotechnology. Controversies over such issues as nuclear waste, genetically modified organisms, asbestos, tobacco, gene therapy, avian flu, and cell phone towers arise almost daily as rapid scientific and technological advances create uncertainty and bring about unforeseen concerns. The authors of Acting in an Uncertain World argue that political institutions must be expanded and improved to manage these controversies, to transform them into productive conversations, and to bring about “technical democracy.” They show how “hybrid forums”—in which experts, non-experts, ordinary citizens, and politicians come together—reveal the limits of traditional delegative democracies, in which decisions are made by quasi-professional politicians and techno-scientific information is the domain of specialists in laboratories. The division between professionals and laypeople, the authors claim, is simply outmoded. The authors argue that laboratory research should be complemented by everyday experimentation pursued in the real world, and they describe various modes of cooperation between the two. They explore a range of concrete examples of hybrid forums that have dealt with sociotechnical controversies including nuclear waste disposal in France, industrial waste and birth defects in Japan, a childhood leukemia cluster in Woburn, Massachusetts, and mad cow disease in the United Kingdom. The authors discuss the implications for political decision making in general and describe a “dialogic” democracy that enriches traditional representative democracy. To invent new procedures for consultation and representation, they suggest, is to contribute to an endless process that is necessary for the ongoing democratization of democracy.
Published in the year 1985, An Elementary Approach To Thinking Under Uncertainty is a valuable contribution to the field of Cognitive Psychology.
The Individualization of War examines the status of individuals in contemporary armed conflict in three main capacities: as subject to violence but deserving of protection; as liable to harm because of their responsibility for attacks on others; and as agents who can be held accountable for the perpetration of crimes.
Daniel Williams shows how, in a profoundly numerical age, Victorian novels imagined thought and action in the face of uncertainty.
Hardbound. How to deal with uncertainty is a subject of much controversy in Artificial Intelligence. This volume brings together a wide range of perspectives on uncertainty, many of the contributors being the principal proponents in the controversy.Some of the notable issues which emerge from these papers revolve around an interval-based calculus of uncertainty, the Dempster-Shafer Theory, and probability as the best numeric model for uncertainty. There remain strong dissenting opinions not only about probability but even about the utility of any numeric method in this context.
Released every three years since March 2003, the United Nations World Water Development Report (WWDR), a flagship UN-Water report published by UNESCO, has become the voice of the United Nations system in terms of the state, use and management of the world's freshwater resources. The report is primarily targeted at national decision-makers and water resource managers, but is also aimed at educating and informing a broader audience, from governments to the private sector and civil society. It underlines the important roles water plays in all social, economic and environmental decisions, highlighting policy implications across various sectors, from local and municipal to regional and international levels. Similarly to the first two editions, this report includes a comprehensive and up-to-date assessment of several key challenge areas, such as water for food, energy and human health, and governance challenges such as institutional reform, knowledge and capacity-building, and financing, each produced by individual UN agencies.
Risk as we now know it is a wholly new phenomenon, the by-product of our ever more complex and powerful technologies. In business, policy making, and in everyday life, it demands a new way of looking at technological and environmental uncertainty. In this definitive volume, four of the world's leading risk researchers present a fundamental critique of the prevailing approaches to understanding and managing risk - the 'rational actor paradigm'. They show how risk studies must incorporate the competing interests, values, and rationalities of those involved and find a balance of trust and acceptable risk. Their work points to a comprehensive and significant new theory of risk and uncertainty and of the decision making process they require. The implications for social, political, and environmental theory and practice are enormous. Winner of the 2000-2002 Outstanding Publication Award of the Section on Environment and Technology of the American Sociological Association
This third volume of eight from the IMAC - XXXII Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Linear Systems Substructure Modelling Adaptive Structures Experimental Techniques Analytical Methods Damage Detection Damping of Materials & Members Modal Parameter Identification Modal Testing Methods System Identification Active Control Modal Parameter Estimation Processing Modal Data