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Welfare Economics and Social Choice Theory ; 2nd ed.
Welfare economics, and social choice theory, are disciplines that blend economics, ethics, political science, and mathematics. Topics in Welfare Economics and Social Choice Theory, 2nd Edition, include models of economic exchange and production, uncertainty, optimality, public goods, social improvement criteria, life and death choices, majority voting, Arrow’s theorem, and theories of implementation and mechanism design.
Web Reasoning and Rule Systems ; 1st International Conference, RR 2007, Innsbruck, Austria, June 7-8, 2007, Proceedings
It address all current topics in Web reasoning and rule systems, including acquisition of rules and ontologies by knowledge extraction, design and analysis of reasoning languages, reasoning with constraints, rule languages and systems, semantic Web services modeling and applications.
Web Reasoning and Rule Systems : 2nd International Conference, RR 2008, Karlsruhe, Germany, October 31-November 1, 2008. Proceedings
This book address all current topics in Web reasoning and rule systems such as acquisition of rules and ontologies by knowledge extraction, design and analysis of reasoning languages, implemented tools and systems, standardization, ontology usability, ontology languages and their relationships, rules and ontologies, reasoning with uncertainty, reasoning with constraints, rule languages and systems, semantic Web services modeling and applications.
Wavelets and Signal Processing : An Application-Based Introduction
As the applications of wavelet transform have spread to diverse areas of signal analysis and compression, students and practitioners need a practical introduction and overview. This textbook provides that concise and practical introduction to the underlying foundations and important applications. Through numerous examples and case studies from industry, it demonstrates both the potential and the limits of wavelet techniques, expanding the usual treatment beyond the discrete wavelet transform to the continuous transform. Providing the basics of Fourier transforms and digital filters in the appendix, the text is supplemented with end-of-chapter exercises, MATLAB code, and a short introduction to the MATLAB wavelet toolbox. Students of electrical engineering and engineers in industry can benefit from the concentration on real applications
Volcanic Unrest : From Science to Society
Volcanic unrest is a complex multi-hazard phenomenon. The fact that unrest may, or may not lead to an imminent eruption contributes significant uncertainty to short-term volcanic hazard and risk assessment. Although it is reasonable to assume that all eruptions are associated with precursory activity of some sort, the understanding of the causative links between subsurface processes, resulting unrest signals and imminent eruption is incomplete. When a volcano evolves from dormancy into a phase of unrest, important scientific, political and social questions need to be addressed. This book is aimed at graduate students, researchers of volcanic phenomena, professionals in volcanic hazard and risk assessment, observatory personnel, as well as emergency managers who wish to learn about the complex nature of volcanic unrest and how to utilize new findings to deal with unrest phenomena at scientific and emergency managing levels.
Validation in Chemical Measurement
Validation of measurement methods has been used for a very ciated measurement uncertainty? The answer must be: no. long time in chemistry. It is mostly based on the examination There can never be a mechanism or recipe for producing - of a measurement procedure for its characteristics such as tomatically valid results because one can never eliminate precision, accuracy, selectivity, sensitivity, repeatability, re- theskills, the role and the responsibility of the analyst. producibility, detectionlimit, quantification limit and more. ISO 9000:2000, item 3. 8. 5 defines validation as confer- When focussing on quality comparability and reliability mation by examination and provision of objective evidence in chemical measurement.
User Modeling 2005 ; 10th International Conference, UM 2005, Edinburgh, Scotland, UK, July 24-29, 2005, Proceedings
The book offers topical sections on adaptive hypermedia, affective computing, data mining for personalization and cross-recommendation, ITS and adaptive advice, modeling and recognizing human activity, multimodality and ubiquitous computing, recommender systems, student modeling, user modeling and interactive systems, and Web site navigation support.
Universal Artificial Intelligence : Sequential Decisions Based on Algorithmic Probability
This book presents sequential decision theory from a novel algorithmic information theory perspective. While the former is suited for active agents in known environments, the latter is suited for passive prediction in unknown environments. The book introduces these two well-known but very different ideas and removes the limitations by unifying them to one parameter-free theory of an optimal reinforcement learning agent embedded in an arbitrary unknown environment. Most if not all AI problems can easily be formulated within this theory, which reduces the conceptual problems to pure computational ones. Considered problem classes include sequence prediction, strategic games, function minimization, reinforcement and supervised learning. The discussion includes formal definitions of intelligence order relations, the horizon problem and relations to other approaches to AI.
Understanding Risks and Uncertainties in Energy and Climate Policy : Multidisciplinary Methods and Tools for a Low Carbon Society
This book analyzes and seeks to consolidate the use of robust quantitative tools and qualitative methods for the design and assessment of energy and climate policies. In particular, it examines energy and climate policy performance and associated risks, as well as public acceptance and portfolio analysis in climate policy, and presents methods for evaluating the costs and benefits of flexible policy implementation as well as new framings for business and market actors. In turn, it discusses the development of alternative policy pathways and the identification of optimal switching points, drawing on concrete examples to do so. Lastly, it discusses climate change mitigation policies’ implications for the agricultural, food, building, transportation, service and manufacturing sectors.
Uncertainty, Rationality, and Agency
This book is about Rational Agents, which can be humans, players in a game, software programs or institutions. Typically, such agents are uncertain about the state of affairs or the state of other agents, and under this partial information they have to decide on which action to take next. This book collects chapters that give formal accounts not only of Uncertainty, Rationality and Agency, but also of their interaction: what are rational criteria to accept certain beliefs, or to modify them; how can degrees of beliefs guide an agent in making decisions; why distinguish between practical and epistemic rationality when agents try to coordinate; what must be common beliefs between agents about each other's rationality in order to act rationally themselves; can an agent assign probabilities to planned actions; how to formalise assumptions about a rational speaker in a conversation obeying Gricean maxims.
Uncertainty Theory
Uncertainty theory is a branch of mathematics based on normality, monotonicity, self-duality, and countable subadditivity axioms. The goal of uncertainty theory is to study the behavior of uncertain phenomena such as fuzziness and randomness. The main topics include probability theory, credibility theory, and chance theory. For this new edition the entire text has been totally rewritten. More importantly, the chapters on chance theory and uncertainty theory are completely new. This book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory. The purpose is to equip the readers with an axiomatic approach to deal with uncertainty. Mathematicians, researchers, engineers, designers, and students in the field of mathematics, information science, operations research, industrial engineering, computer science, artificial intelligence, and management science will find this work a stimulating and useful reference.
Uncertainty Reasoning for the Semantic Web I ; ISWC International Workshops, URSW 2005-2007, Revised Selected and Invited Papers
Represents the first comprehensive compilation of state-of-the-art research approaches to uncertainty reasoning in the context of the semantic Web, capturing different models of uncertainty and approaches to deductive as well as inductive reasoning with uncertain formal knowledge.
Uncertainty in the Electric Power Industry : Methods and Models for Decision Support
Examines the uncertainties power companies are facing and develops models to describe them – including an innovative approach combining fundamental and finance models for price modeling. The optimization of generation and trading portfolios under uncertainty is discussed with particular focus on CHP and is linked to risk management. Here the concept of integral earnings at risk is developed to provide a theoretically sound combination of value at risk and profit at risk approaches, adapted to real market structures and market liquidity. Also methods for supporting long-term investment decisions are presented: technology assessment based on experience curves and operation simulation for fuel cells and a real options approach with endogenous electricity prices.
Uncertainty in Mechanical Engineering ; Proceedings of the 4th International Conference on Uncertainty in Mechanical Engineering (ICUME 2021), June 7–8, 2021
Reports on methods and technologies to describe, evaluate and control uncertainty in mechanical engineering applications. It brings together contributions by engineers, mathematicians and legal experts, offering a multidisciplinary perspective on the main issues affecting uncertainty throughout the complete system lifetime, which includes process and product planning, development, production and usage. The book is based on the proceedings of the 4th International Conference on Uncertainty in Mechanical Engineering (ICUME 2021), organized by the Collaborative Research Center (CRC) 805 of the TU Darmstadt, and held online on June 7–8, 2021. All in all, it offers a timely resource for researchers, graduate students and practitioners in the field of mechanical engineering, production engineering and engineering optimization.
Uncertainty in Engineering : Introduction to Methods and Applications
Provides an introduction to uncertainty quantification in engineering. Starting with preliminaries on Bayesian statistics and Monte Carlo methods, followed by material on imprecise probabilities, it then focuses on reliability theory and simulation methods for complex systems. The final two chapters discuss various aspects of aerospace engineering, considering stochastic model updating from an imprecise Bayesian perspective, and uncertainty quantification for aerospace flight modelling.
Uncertainty Forecasting in Engineering
Deals with uncertainty forecasting based on a fuzzy time series approach, including fuzzy random processes and artificial neural networks. A consideration of data and measurement uncertainty enhances forecasting in a wide range of applications, particularly in the fields of engineering, environmental science and civil engineering.Uncertain data are described by means of a new incremental fuzzy representation which permits a complete and accurate estimation of uncertainty.
Uncertainty Assessment of Large Finite Element Systems
The treatment of uncertainties in the analysis of engineering structures remains one of the premium challenges in structural mechanics. It is only in recent years that the developments in stochastic and deterministic computational mechanics began to be synchronized. In this monograph novel computational procedures for the uncertainty assessment of large finite element systems are presented. The procedures are applicable to well known problems in computational stochastic mechanics, such as the stability analysis of systems with random imperfections and the dynamic analysis of deterministic systems under stochastic loading. For the dynamic analysis of deterministic systems under stochastic loading, an efficient procedure based on the Karhunen-Loève representation of the response is presented. The capabilities of the developed procedures are demonstrated with several numerical examples.
Uncertainty and Surprise in Complex Systems : Questions on Working with the Unexpected
This book is the outcome of a discussion meeting of leading scholars and critical thinkers with expertise in complex systems sciences and leaders from a variety of organizations sponsored by the Prigogine Center at The University of Texas at Austin and the Plexus Institute to explore strategies for understanding uncertainty and surprise. Besides distributions to the conference it includes a key digest by the editors as well as a commentary by the late nobel laureat Ilya Prigogine, "Surprises in half of a century". The book is intended for researchers and scientists in complexity science as well as for a broad interdisciplinary audience of both practitioners and scholars. It will well serve those interested in the research issues and in the application of complexity science to physical and social systems.
Uncertainty and Risk : Mental, Formal, Experimental Representations
This book tries to sort out the different meanings of uncertainty and to discover their foundations. It shows that uncertainty can be represented using various tools and mental guidelines. Some decision criteria are then related to each case and assessed. Alternative ways to deal with risk - and risk attitude concepts - are then examined in the above perspective. Behavior under uncertainty emerges from this book as something to base more on inquiry and reflection than on mere intuition.
Type-2 Fuzzy Logic : Theory and Applications
Describes new methods for building intelligent systems using type-2 fuzzy logic and soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including type-1 fuzzy logic, neural networks, and genetic algorithms, which can be used to create powerful hybrid intelligent systems. The authors extends the use of fuzzy logic to a higher order, which is called type-2 fuzzy logic. Combining type-2 fuzzy logic with traditional SC techniques, we can build powerful hybrid intelligent systems that can use the advantages that each technique offers. We consider in this book the use of type-2 fuzzy logic and traditional SC techniques to solve pattern recognition problems in realworld applications.
