Conditional Logic In Expert Systems
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Conditional Logic In Expert Systems
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Author : Irwin R. Goodman
language : en
Publisher: North Holland
Release Date : 1991
Conditional Logic In Expert Systems written by Irwin R. Goodman and has been published by North Holland this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Business & Economics categories.
This volume is a collection of invited papers on all basic aspects of conditional logic, inference and reasoning in expert systems. Specifically, theoretical results and applications centered around the main task in automated reasoning, namely conditional inference, in the three main approaches to reasoning under uncertainty (Bayesian, Fuzzy sets and Belief functions) including: - Measure-free conditioning, conditioning operators for non-monotonic reasoning; - General approach using logic to conditional inference; - Conditioning reasoning with fuzzy sets; - Random set as a formalism for evidential reasoning; - New results in the theory of Belief functions; - Some aspects of applications to various fields of AI.
Conditional Inference And Logic For Intelligent Systems
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Author : Irwin R. Goodman
language : en
Publisher: North Holland
Release Date : 1991
Conditional Inference And Logic For Intelligent Systems written by Irwin R. Goodman and has been published by North Holland this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Business & Economics categories.
This work is concerned with addressing an anomoly involving probability and logic. This includes the interpretation and evaluation of implicative statements in natural language, compatible with conditional probability. One of the chief motivations for investigating this problem has been the need to formalize rigorously the appropriate connections between conditional probabilities and the underlying production rules in expert sytems. This is accomplished through the development of a comprehensive theory of conditional events and an associated logic. The results of this effort should be of prime use in the design and evaluation of inference rules in expert systems, and also, allow for a new expansion of probability to include at the syntactic level the concept of conditioning. The monograph is intended for two audiences: AI researchers who are primarily interested in the management of uncertainty in expert systems, and mathematicians in the fields of probabilistic modeling, logic, and algebra.
Reasoning With Actual And Potential Contradictions
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Author : Dov M. Gabbay
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Reasoning With Actual And Potential Contradictions written by Dov M. Gabbay and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Philosophy categories.
We are happy to present the second volume of the Handbook of Defeasible Reasoning and Uncertainty Management Systems. Uncertainty pervades the real world and must therefore be addressed by every system that attempts to represent reality. The representation of un certainty is a major concern of philosophers, logicians, artificial intelligence researchers and computer sciencists, psychologists, statisticians, economists and engineers. The present Handbook volumes provide frontline coverage of this area. This Handbook was produced in the style of previous handbook series like the Handbook of Philosophical Logic, the Handbook of Logic in Computer Science, the Handbook of Logic in Artificial Intelligence and Logic Programming, and can be seen as a companion to them in covering the wide applications of logic and reasoning. We hope it will answer the needs for adequate representations of uncertainty. This Handbook series grew out of the ESPRIT Basic Research Project DRUMS II, where the acronym is made out of the Handbook series title. This project was financially supported by the European Union and regroups 20 major European research teams working in the general domain of uncer tainty. As a fringe benefit of the DRUMS project, the research community was able to create this Handbook series, relying on the DRUMS partici pants as the core of the authors for the Handbook together with external international experts.
Uncertain Information Processing In Expert Systems
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Author : Petr Hajek
language : en
Publisher: CRC Press
Release Date : 1992-06-29
Uncertain Information Processing In Expert Systems written by Petr Hajek and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-06-29 with Computers categories.
Uncertain Information Processing in Expert Systems systematically and critically examines probabilistic and rule-based (compositional, MYCIN-like) systems, the two most important families of expert systems dealing with uncertainty. The book features a detailed introduction to probabilistic systems (including methods using graphical models and methods of knowledge integration), an analysis of compositional systems based on algebraic considerations, an application of graphical models, and the Dempster-Shafer theory of evidence and its use in expert systems. The book will be useful to anyone working in artificial intelligence, statistical computing, symbolic logic, and expert systems.
Learning And Modeling With Probabilistic Conditional Logic
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Author : Jens Fisseler
language : en
Publisher: IOS Press
Release Date : 2010
Learning And Modeling With Probabilistic Conditional Logic written by Jens Fisseler and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Artificial intelligence categories.
Conditionals, also called if-then-rules, are a popular concept for knowledge representation. They have intuitive semantics and can also be annotated with probabilities, which, when combined with the principle of maximum entropy, yields a powerful formalism for representing uncertain knowledge. This dissertation discusses several issues pertaining to probabilistic conditionals: learning them from data and using them for modeling. The first part of this thesis presents the implementation of a method for learning probabilistic conditionals from data. In the second part, this learning technique is applied to the problem of fusing data originating from different sources. The third part is the focal point of the thesis. Here, an extension of a propositional probabilistic conditional logic to a first-order probabilistic conditional logic is developed and an approach to reduce the complexity of computing the maximum entropy model of a set of first-order probabilistic conditionals is devised. IOS Press is an international science, technical and medical publisher of high-quality books for academics, scientists, and professionals in all fields. Some of the areas we publish in: -Biomedicine -Oncology -Artificial intelligence -Databases and information systems -Maritime engineering -Nanotechnology -Geoengineering -All aspects of physics -E-governance -E-commerce -The knowledge economy -Urban studies -Arms control -Understanding and responding to terrorism -Medical informatics -Computer Sciences
Mathematical Models For Handling Partial Knowledge In Artificial Intelligence
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Author : Giulianella Coletti
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Mathematical Models For Handling Partial Knowledge In Artificial Intelligence written by Giulianella Coletti and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Mathematics categories.
Knowledge acquisition is one of the most important aspects influencing the quality of methods used in artificial intelligence and the reliability of expert systems. The various issues dealt with in this volume concern many different approaches to the handling of partial knowledge and to the ensuing methods for reasoning and decision making under uncertainty, as applied to problems in artificial intelligence. The volume is composed of the invited and contributed papers presented at the Workshop on Mathematical Models for Handling Partial Knowledge in Artificial Intelligence, held at the Ettore Majorana Center for Scientific Culture of Erice (Sicily, Italy) on June 19-25, 1994, in the framework of the International School of Mathematics "G.Stampacchia". It includes also a transcription of the roundtable held during the workshop to promote discussions on fundamental issues, since in the choice of invited speakers we have tried to maintain a balance between the various schools of knowl edge and uncertainty modeling. Choquet expected utility models are discussed in the paper by Alain Chateauneuf: they allow the separation of perception of uncertainty or risk from the valuation of outcomes, and can be of help in decision mak ing. Petr Hajek shows that reasoning in fuzzy logic may be put on a strict logical (formal) basis, so contributing to our understanding of what fuzzy logic is and what one is doing when applying fuzzy reasoning.
Frontiers Of Expert Systems
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Author : Chilukuri Krishna Mohan
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Frontiers Of Expert Systems written by Chilukuri Krishna Mohan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
The development of modern knowledge-based systems, for applications ranging from medicine to finance, necessitates going well beyond traditional rule-based programming. Frontiers of Expert Systems: Reasoning with Limited Knowledge attempts to satisfy such a need, introducing exciting and recent advances at the frontiers of the field of expert systems. Beginning with the central topics of logic, uncertainty and rule-based reasoning, each chapter in the book presents a different perspective on how we may solve problems that arise due to limitations in the knowledge of an expert system's reasoner. Successive chapters address (i) the fundamentals of knowledge-based systems, (ii) formal inference, and reasoning about models of a changing and partially known world, (iii) uncertainty and probabilistic methods, (iv) the expression of knowledge in rule-based systems, (v) evolving representations of knowledge as a system interacts with the environment, (vi) applying connectionist learning algorithms to improve on knowledge acquired from experts, (vii) reasoning with cases organized in indexed hierarchies, (viii) the process of acquiring and inductively learning knowledge, (ix) extraction of knowledge nuggets from very large data sets, and (x) interactions between multiple specialized reasoners with specialized knowledge bases. Each chapter takes the reader on a journey from elementary concepts to topics of active research, providing a concise description of several topics within and related to the field of expert systems, with pointers to practical applications and other relevant literature. Frontiers of Expert Systems: Reasoning with Limited Knowledge is suitable as a secondary text for a graduate-level course, and as a reference for researchers and practitioners in industry.
Probabilistic Methods In Expert Systems
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Author : Romano Scozzafava
language : en
Publisher:
Release Date : 1993
Probabilistic Methods In Expert Systems written by Romano Scozzafava and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Expert systems (Computer science) categories.
Conditionals Information And Inference
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Author : Gabriele Kern-Isberner
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-05-18
Conditionals Information And Inference written by Gabriele Kern-Isberner and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-05-18 with Computers categories.
This book constitutes the thoroughly refereed postproceedings of the International Workshop on Conditionals, Information, and Inference, WCII 2002, held in Hagen, Germany in May 2002. The 9 revised full papers presented together with 3 invited papers by leading researchers in the area were carefully selected during iterated rounds of reviewing and improvement. The papers address all current issues of research on conditionals, ranging from foundational, theoretical, and methodological aspects to applications in various contexts of knowledge representation.
Conditionals In Nonmonotonic Reasoning And Belief Revision
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Author : Gabriele Kern-Isberner
language : en
Publisher: Springer
Release Date : 2003-06-29
Conditionals In Nonmonotonic Reasoning And Belief Revision written by Gabriele Kern-Isberner and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-06-29 with Computers categories.
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.