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The Belief Formula: The Secret to Unlocking the Power of Prayer is an amazing look at the role of the human mind, thought patterns, and the very real power of belief, in the creation process - a continuous process which produces every single moment of your life "according to your thoughts." Most of us grew up being told what to think, believe, and do, but not how to think and believe. The Belief Formula will teach you how you can live the life of your dreams, and how to find what you seek in life. The Belief Formula makes practical sense out of ancient principles, and demonstrates how the latest medical and scientific research offers clinical evidence that our thoughts create our physiology, and every part of our existence. Most people are not aware that there is more than one way to think, and that they unconsciously spend most of the day operating in the least effective part of their brain.
This is a collection of classic research papers on the Dempster-Shafer theory of belief functions. The book is the authoritative reference in the field of evidential reasoning and an important archival reference in a wide range of areas including uncertainty reasoning in artificial intelligence and decision making in economics, engineering, and management. The book includes a foreword reflecting the development of the theory in the last forty years.
This book constitutes the refereed proceedings of the 7th International Conference on Belief Functions, BELIEF 2022, held in Paris, France, in October 2022. The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well-understood connections to other frameworks such as probability, possibility, and imprecise probability theories. It has been applied in diverse areas such as machine learning, information fusion, and pattern recognition. The 29 full papers presented in this book were carefully selected and reviewed from 31 submissions. The papers cover a wide range on theoretical aspects on mathematical foundations, statistical inference as well as on applications in various areas including classification, clustering, data fusion, image processing, and much more.
This book constitutes the refereed proceedings of the 6th International Conference on Belief Functions, BELIEF 2021, held in Shanghai, China, in October 2021. The 30 full papers presented in this book were carefully selected and reviewed from 37 submissions. The papers cover a wide range on theoretical aspects on mathematical foundations, statistical inference as well as on applications in various areas including classification, clustering, data fusion, image processing, and much more.
This six-volume set presents cutting-edge advances and applications of expert systems. Because expert systems combine the expertise of engineers, computer scientists, and computer programmers, each group will benefit from buying this important reference work. An "expert system" is a knowledge-based computer system that emulates the decision-making ability of a human expert. The primary role of the expert system is to perform appropriate functions under the close supervision of the human, whose work is supported by that expert system. In the reverse, this same expert system can monitor and double check the human in the performance of a task. Human-computer interaction in our highly complex world requires the development of a wide array of expert systems. Expert systems techniques and applications are presented for a diverse array of topics including Experimental design and decision support The integration of machine learning with knowledge acquisition for the design of expert systems Process planning in design and manufacturing systems and process control applications Knowledge discovery in large-scale knowledge bases Robotic systems Geograhphic information systems Image analysis, recognition and interpretation Cellular automata methods for pattern recognition Real-time fault tolerant control systems CAD-based vision systems in pattern matching processes Financial systems Agricultural applications Medical diagnosis
This book, from the perspective of reliability science construction, proposes a new theory called BELIEF RELIABILITY theory on the basis of probability theory, uncertainty theory and chance theory. The main topics include the philosophical basis of reliability science, the principles of reliability science, the criteria of reasonable reliability metrics and the basic theoretical framework and methodology of belief reliability theory. In this book, the belief reliability metric, analysis, design and evaluation methods will provide readers with a brand-new perspective on reliability applications and uncertainty quantification.
A wide-ranging study of the central concepts in epistemology - belief, truth and knowledge. Professor Armstrong offers a dispositional account of general beliefs and of knowledge of general propositions. Belief about particular matters of fact are described as structures in the mind of the believer which represent or 'map' reality, while general beliefs are dispositions to extend the 'map' or introduce casual relations between portions of the map according to general rules. 'Knowledge' denotes the reliability of such beliefs as representations of reality. Within this framework Professor Armstrong offers a distinctive account of many of the main questions in general epistemology - the relations between beliefs and language, the notions of proposition, concept and idea, the analysis of truth, the varieties of knowledge, and the way in which beleifs and knowledge are supported by reasons. The book as a whole if offered as a contribution to a naturalistic account of man.
Belief revision theory and philosophy of science both aspire to shed light on the dynamics of knowledge – on how our view of the world changes (typically) in the light of new evidence. Yet these two areas of research have long seemed strangely detached from each other, as witnessed by the small number of cross-references and researchers working in both domains. One may speculate as to what has brought about this surprising, and perhaps unfortunate, state of affairs. One factor may be that while belief revision theory has traditionally been pursued in a bottom- up manner, focusing on the endeavors of single inquirers, philosophers of science, inspired by logical empiricism, have tended to be more interested in science as a multi-agent or agent-independent phenomenon.
Conditionals are omnipresent, in everyday life as well as in scientific environments; they represent generic knowledge acquired inductively or learned from books. They tie a flexible and highly interrelated network of connections along which reasoning is possible and which can be applied to different situations. Therefore, conditionals are important, but also quite problematic objects in knowledge representation. This book presents a new approach to conditionals which captures their dynamic, non-proportional nature particularly well by considering conditionals as agents shifting possible worlds in order to establish relationships and beliefs. This understanding of conditionals yields a rich theory which makes complex interactions between conditionals transparent and operational. Moreover,it provides a unifying and enhanced framework for knowledge representation, nonmonotonic reasoning, belief revision,and even for knowledge discovery.