الصفحة 7
الصفحة 7
Machine Learning and Probabilistic Graphical Models for Decision Support Systems
Presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.
Logistics Systems Analysis
It has two new sections, a new appendix, and more than half a dozen new figures. A few references have also been added, Much of the new material is based on work , The financial support of the National Science Foundation and the Volvo Foundations Center of Excellence for the Future of Urban Transportation at U. C. Berkeley is also acknowledged. The new appendix presents the logic behind the traveling salesman and vehicle routing results used in Sec. 4. 2 to describe the transportation ope- tion; Chapter 4 is more self-contained as a result. New section 5. 6 int- duces and evaluates a general method that automatically translates the c- tinuum approximation recipes of Chapters 4 and 5 into discrete system designs. This closes a gap in previous editions. Other additions include an explanation of how to develop system designs that can efficiently acc- modate real-time control strategies to manage uncertainty (new section 4. 6. 3), and extensions of the many-to-many design ideas of Chap. 6
Logic, Thought and Action
Contribute to our understanding of this dynamic process by clearly presenting and discussing the most important hypotheses, issues and theories in philosophical and logical study of language, thought and action. Among the fundamental issues discussed are the rationality and freedom of agents, theoretical and practical reasoning, individual and collective attitudes and actions, the nature of cooperation and communication, the construction and conditions of adequacy of scientific theories, propositional contents and their truth conditions, illocutionary force, time, aspect and presupposition in meaning, speech acts within dialogue, the dialogical approach to logic and the structure of dialogues and other language games, as well as formal methods needed in logic or artificial intelligence to account for choice, paradoxes, uncertainty and imprecision.
Learning and Adaption in Multi-Agent Systems ; 1st International Workshop, LAMAS 2005, Utrecht, The Netherlands, July 25, 2005, Revised Selected Papers
Contains selected and revised papers of the International Workshop on Lea- ing and Adaptation in Multi-Agent Systems (LAMAS 2005), held at the AAMAS 2005 Conference in Utrecht, The Netherlands, July 26. An important aspect in multi-agent systems (MASs) is that the environment evolves over time, not only due to external environmental changes but also due to agent int- actions. For this reason it is important that an agent can learn, based on experience, and adapt its knowledge to make rational decisions and act in this changing environment autonomously. Machine learning techniques for single-agent frameworks are well established. Agents operate in uncertain environments and must be able to learn and act - tonomously. This task is, however, more complex when the agent interacts with other agents that have potentially different capabilities and goals. The single-agent case is structurally different from the multi-agent case due to the added dimension of dynamic interactions between the adaptive agents. Multi-agent learning, i.e., the ability of the agents to learn how to cooperate and compete, becomes crucial in many domains. Autonomous agents and multi-agent systems (AAMAS) is an emerging multi-disciplinary area encompassing computer science, software engineering, biology, as well as cognitive and social sciences. A t- oretical framework, in which rationality of learning and interacting agents can be - derstood, is still under development in MASs, although there have been promising ?
Leading in a VUCA World : Integrating Leadership, Discernment and Spirituality
Brings together works by specialists from different disciplines and continents to reflect on the nexus between leadership, spirituality and discernment, particularly with regard to a world that is increasingly volatile, uncertain, complex, and ambiguous (VUCA). The book spells out, first of all, what our VUCA world entails, and how it affects businesses, organizations, and societies as a whole. Secondly, the book develops new perspectives on the processes of leadership, spirituality, and discernment, particularly in this VUCA context. These perspectives are interdisciplinary in nature, and are informed by e.g. management studies, leadership theory, philosophy, and theology.
L’insuffisance rénale aiguë = Acute renal failure
The aim of this book is to make current data from the experimental and clinical literature accessible to readers. More than a thousand articles are published each year on the theme and the authors aim to synthesize this information. These data relate in particular to the identification of early markers of renal dysfunction without which screening, recognition of the main pathophysiological determinants and prevention remain uncertain. This book focuses attention on clinical situations characterized by the renal impact of the main dysfunctions of vital functions, the prognosis of which is worsened by the occurrence of this renal failure. The following will be treated in particular: the renal consequences of oxidative stress, the renal consequences of respiratory dysfunction, cardiac dysfunction, hepatic dysfunction, alterations in hemostasis, septic shock and hemorrhagic shock. Finally, the physiopathological data from experimental models are gradually finding their echo in the clinical field, opening up therapeutic avenues whose recent evaluations will be analyzed.
Justifying the Dependability of Computer-based Systems : With Applications in Nuclear Engineering
The book also explores some of the more fundamental aspects of safety evaluation, such as the nature of models, arguments, evidence and documentation, and the ways to deal with different types of risk and uncertainty. Justifying the Dependability of Computer-based Systems will be of value to software, computer system, instrumentation and control engineers, and regulators working in industry sectors such as nuclear safety.
Iutam Symposium on Dynamics and Control of Nonlinear Systems with Uncertainty ; Proceedings of the IUTAM Symposium held in Nanjing, China, September 18-22, 2006
The last decade has witnessed an increasing interest towards the dynamics and control of nonlinear engineering systems from the scientists engaged in nonlinear dynamics and the control engineers. Both groups of people have recognized the importance of interaction between nonlinear dynamics and robust control during their efforts to improve the dynamic performance of engineering systems with uncertainty, which comes from either the random excitations, such as wind and earthquake, or the modelling errors of real systems including their sensors, controllers and actuators. The dynamics and control of nonlinear systems with uncertainty, therefore, is a vital interdisciplinary topic related to both stochastic systems and deterministic systems. This volume contains the papers presented at the IUTAM Symposium on Dynamics and Control of Nonlinear Systems with Uncertainty, which was sponsored by the International Union of Theoretical and Applied Mechanics (IUTAM)
Iterative Learning Control : Robustness and Monotonic Convergence for Interval Systems
This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. Two key problems with the fundamentals of iterative learning control (ILC) design as treated by existing work are: first, many ILC design strategies assume nominal knowledge of the system to be controlled and; second, it is well-known that many ILC algorithms do not produce monotonic convergence, though in applications monotonic convergence is often essential. Iterative Learning Control takes account of the recently-developed comprehensive approach to robust ILC analysis and design established to handle the situation where the plant model is uncertain. Considering ILC in the iteration domain, it presents a unified analysis and design framework that enables designers to consider both robustness and monotonic convergence for typical uncertainty models, including parametric interval uncertainties, iteration-domain frequency uncertainty, and iteration-domain stochastic uncertainty.
Complex decision making : Theory and practice
The increasingly complex environment of today's world, characterized by technological innovation and global communication, generates myriads of possible and actual interactions while limited physical and intellectual resources severely impinge on decision makers, be it in the public or private domains. At the core of the decision-making process is the need for quality information that allows the decision maker to better assess the impact of decisions in terms of outcomes, nonlinear feedback processes and time delays on the performance of the complex system invoked.
Climate Change Impacts for the Conterminous USA : An Integrated Assessment
In this volume, an improved Integrated Assessment methodology is used to analyse climate change impacts on agriculture, water resources, unmanaged ecosystems, irrigation, and land use in the United States and the economic implications of these impacts. This book contains a series of papers documenting the methods, models, analysis and results of this integrated assessment for a wide ranging set of scenarios describing future climate change. Innovations described include the integration of water resource and agricultural modeling and the refinement of an agriculture and land-use economics model to incorporate results from process-level ecosystem models of agriculture, water and natural ecosystem resources. Scenarios selected for this study address a range of uncertainties associated with choice of climate model, presence or absence of a ‘CO2-fertilization effect’, impacts on international trade in agricultural commodities and their consequences for producers and consumers.
Classification and Clustering for Knowledge Discovery
This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. In its first part the book provides a collection of recent research on distributed clustering, self organizing maps and their recent extensions. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees. Therefore this book presents a collection of important methods of supervised data analysis. "Classification and Clustering for Knowledge Discovery" also includes variety of applications of knowledge discovery in health, safety, commerce, mechatronics, sensor networks, and telecommunications.
Classic Works on the Dempster-Shafer Theory of Belief Functions
This book brings together a collection of classic research papers on the Dempster-Shafer theory of belief functions. By bridging fuzzy logic and probabilistic reasoning, the theory of belief functions has become a primary tool for knowledge representation and uncertainty reasoning in expert systems.
Childlessness in Europe : Contexts, Causes, and Consequences
This open access book provides an overview of childlessness throughout Europe. It offers a collection of papers written by leading demographers and sociologists that examine contexts, causes, and consequences of childlessness in countries throughout the region.The book features data from all over Europe. It specifically highlights patterns of childlessness in Germany, France, the United Kingdom, Finland, Sweden, Austria and Switzerland. An additional chapter on childlessness in the United States puts the European experience in perspective.
Chemical Youth : Navigating Uncertainty in Search of the Good Life
This book explores how young people engage with chemical substances in their everyday lives. It builds upon and supplements a large body of literature on young people’s use of drugs and alcohol to highlight the subjectivities and socialities that chemical use enables across diverse socio-cultural settings, illustrating how young people seek to avoid harm, while harnessing the beneficial effects of chemical use.
Chance Discoveries in Real World Decision Making : Data-based Interaction of Human intelligence and Artificial Intelligence
For this book, the editors invited and called for contributions from indispensable research areas relevant to "chance discovery," which has been defined as the discovery of events significant for making a decision, and studied since 2000. From respective research areas as artificial intelligence, mathematics, cognitive science, medical science, risk management, methodologies for design and communication, the invited and selected authors in this book present their particular approaches to chance discovery. The chapters here show contributions to identifying rare or hidden events and explaining their significance, predicting future trends, communications for scenario development in marketing and design, identification effects and side-effects of medicines, etc.
Catastrophe modeling : A new approach to managing risk
Catastrophe Modeling: A New Approach to Managing Risk is the first book that systematically analyzes how catastrophe models can be used for assessing and managing risks of extreme events. It focuses on natural disaster risk, but also discusses the management of terrorism risk. A unique feature of this book is the involvement of three leading catastrophe modeling firms, AIR Worldwide, EQECAT, and Risk Management Solutions, who examine the role of catastrophe modeling in rate setting, portfolio management and risk financing. Given the uncertainties associated with terrorism the book points out the opportunities for utilizing catastrophe models to set insurance rates and to examine public-private partnerships for providing financial assistance in the event of a terrorist attack. This book is strongly recommended for individuals who must make decisions regarding the management of impacts of catastrophe risks including those in both the public and private sector.
Catalogue of risks : Natural, technical, social and health risks
The book clearly shows the interdependence of risk measures. Safety and risks cannot be discussed only by looking at specific problems, since increasing safety in individual fields might lead to a decrease of safety over the entire society.
Case-Based Approximate Reasoning
Case-based reasoning (CBR) has received a great deal of attention in recent years and has established itself as a core methodology in the field of artificial intelligence. The key idea of CBR is to tackle new problems by referring to similar problems that have already been solved in the past. More precisely, CBR proceeds from individual experiences in the form of cases. The generalization beyond these experiences typically relies on a kind of regularity assumption demanding that 'similar problems have similar solutions'. Making use of different frameworks of approximate reasoning and reasoning under uncertainty, notably probabilistic and fuzzy set-based techniques, this book develops formal models of the above inference principle, which is fundamental to CBR. The case-based approximate reasoning methods thus obtained especially emphasize the heuristic nature of case-based inference and aspects of uncertainty in CBR. This way, the book contributes to a solid foundation of CBR which is grounded on formal concepts and techniques from the aforementioned fields. Besides, it establishes interesting relationships between CBR and approximate reasoning, which not only cast new light on existing methods but also enhance the development of novel approaches and hybrid systems.
Cancer Survivorship : Today and Tomorrow
A diagnosis of cancer provokes myriad responses in patients, chief among them the question: "how long do I have to live?" Increasingly, the answer to that question is not one of months or years, but decades. While there are now nearly 10 million people in the United States who have recovered or are currently recovering from cancer (increased from three million in 1971), the unique challenges encountered by survivors are often met with uncertainity by even the most seasoned physicians, nurses, and clinical social workers because of a lack of formal guidelines for post-treatment care and follow-up.
