Solving practical problems often requires the integration of information and knowledge from many different sources, taking into account uncertainty and impreciseness. The 2010 International Symposium on Integrated Uncertainty Management and Applications (IUM’2010), which takes place at the Japan Advanced Institute of Science and Technology (JAIST), Ishikawa, Japan, between 9th–11th April, is therefore conceived as a forum for the discussion and exchange of research results, ideas for and experience of application among researchers and practitioners involved with all aspects of uncertainty modelling and management.

This book constitutes the refereed proceedings of the 4th International Symposium on Integrated Uncertainty in Knowledge Modeling and Decision Making, IUKM 2015, held in Nha Trang, Vietnam, in October 2015. The 40 revised full papers were carefully reviewed and selected from 58 submissions and are presented together with three keynote and invited talks. The papers provide a wealth of new ideas and report both theoretical and applied research on integrated uncertainty modeling and management

This volume integrates scholarly work on disclosure and uncertainty with the most up-to-date, cutting edge research, theories, and applications. Uncertainty is an ever-present part of human relationships, and the ways in which people reduce and/or manage uncertainty involves regulating their communication with others through revealing and concealing information. This collection is devoted to collating knowledge in these areas, advancing theory and presenting work that is socially meaningful. This work includes contributions from renowned scholars in interpersonal uncertainty and information regulation, focusing on processes that bridge boundaries within and across disciplines, while maintaining emphasis on interpersonal contexts. Disciplines represented here include interpersonal, family, and health communication, as well as relational and social psychology. Key features of the volume include: comprehensive coverage integrating the latest research on disclosure, information seeking, and uncertainty a highly theoretical content, socially meaningful in nature (applied to real-world contexts) an interdisciplinary approach that crosses sub-fields within communication. This volume is a unique and timely resource for advanced study in interpersonal, health, or family communication. With its emphasis on theory, the book is an excellent resource for graduate courses addressing theory and/or theory construction, and it will also appeal to scholars interested in applied research.

Since the emergence of the formal concept of probability theory in the seventeenth century, uncertainty has been perceived solely in terms of probability theory. However, this apparently unique link between uncertainty and probability theory has come under investigation a few decades back. Uncertainties are nowadays accepted to be of various kinds. Uncertainty in general could refer to different sense like not certainly known, questionable, problematic, vague, not definite or determined, ambiguous, liable to change, not reliable. In Indian languages, particularly in Sanskrit-based languages, there are other higher levels of uncertainties. It has been shown that several mathematical concepts such as the theory of fuzzy sets, theory of rough sets, evidence theory, possibility theory, theory of complex systems and complex network, theory of fuzzy measures and uncertainty theory can also successfully model uncertainty.

Winner of the 2017 NCA Gerald R. Miller Book Award! Use and Understand Interpersonal Communication Theories Engaging Theories in Interpersonal Communication: Multiple Perspectives highlights key theories used to guide interpersonal communication research. The Second Edition features 30 theory chapters written by leading scholars in interpersonal communication, including new coverage of evolutionary theories, Problematic Integration Theory, supportive communication theories, Theory of Motivated Information Management, critical approaches to interpersonal communication, and Media Multiplexity Theory. Each theory chapter follows the same structure to help readers easily find and compare information across theories. An updated introductory chapter maps the history and the current state of interpersonal communication theory since publication of the first edition, based on comprehensive analysis of published scholarship. Presenting both classic and cutting-edge issues, the book organizes theories into three clusters—theories that are individually-centered; theories that are focused on discourse and interaction processes; and theories that examine how communication functions in personal relationships. All authors interweave abstract theoretical concepts with concrete examples in order to maximize readability and comprehension.

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.

This volume contains the papers presented at the Third International Conference on Scalable Uncertainty Management, SUM 2009, in Washington, DC, September 28-30, 2009. It contains 21 technical papers which were selected out of 30 submitted papers in a rigourous reviewing process. The volume also contains extended abstracts of two invited talks. The volume reflects the growing interest in uncertainty and incosistency and aims at bringing together all those interested in the management of uncertainty and inconsistency at large.