Foundations Of Reasoning Under Uncertainty
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Subjective Logic
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Author : Audun Jøsang
language : en
Publisher: Springer
Release Date : 2016-10-27
Subjective Logic written by Audun Jøsang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-27 with Computers categories.
This is the first comprehensive treatment of subjective logic and all its operations. The author developed the approach, and in this book he first explains subjective opinions, opinion representation, and decision-making under vagueness and uncertainty, and he then offers a full definition of subjective logic, harmonising the key notations and formalisms, concluding with chapters on trust networks and subjective Bayesian networks, which when combined form general subjective networks. The author shows how real-world situations can be realistically modelled with regard to how situations are perceived, with conclusions that more correctly reflect the ignorance and uncertainties that result from partially uncertain input arguments. The book will help researchers and practitioners to advance, improve and apply subjective logic to build powerful artificial reasoning models and tools for solving real-world problems. A good grounding in discrete mathematics is a prerequisite.
Probabilistic Reasoning In Intelligent Systems
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Author : Judea Pearl
language : en
Publisher: Morgan Kaufmann
Release Date : 1988-09
Probabilistic Reasoning In Intelligent Systems written by Judea Pearl and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988-09 with Computers categories.
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
Foundations Of Reasoning Under Uncertainty
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Author : Bernadette Bouchon-Meunier
language : en
Publisher: Springer
Release Date : 2010-10-22
Foundations Of Reasoning Under Uncertainty written by Bernadette Bouchon-Meunier and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-22 with Computers categories.
Uncertainty exists almost everywhere, except in the most idealized situations; it is not only an inevitable and ubiquitous phenomenon, but also a fundamental sci- ti?c principle. Furthermore, uncertainty is an attribute of information and, usually, decision-relevant information is uncertain and/or imprecise, therefore the abilities to handle uncertain information and to reason from incomplete knowledge are c- cial features of intelligent behaviour in complex and dynamic environments. By carefully exploiting our tolerance for imprecision and approximation we can often achieve tractability, robustness, and better descriptions of reality than traditional - ductive methods would allow us to obtain. In conclusion, as we move further into the ageofmachineintelligence,theproblemofreasoningunderuncertainty,in other words, drawing conclusions from partial knowledge, has become a major research theme. Not surprisingly,the rigoroustreatment of uncertaintyrequiressophisticated - chinery, and the present volume is conceived as a contribution to a better und- standing of the foundations of information processing and decision-making in an environment of uncertainty, imprecision and partiality of truth. This volume draws on papers presented at the 2008 Conference on Information Processing and Management of Uncertainty (IPMU), held in Malaga, ́ Spain, or- nized by the University of Mal ́ aga. The conference brought together some of the world’s leading experts in the study of uncertainty.
The Evidential Foundations Of Probabilistic Reasoning
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Author : David A. Schum
language : en
Publisher: Northwestern University Press
Release Date : 2001
The Evidential Foundations Of Probabilistic Reasoning written by David A. Schum and has been published by Northwestern University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with History categories.
In this work Schum develops a general theory of evidence as it is understood and applied across a broad range of disciplines and practical undertakings. He include insights from law, philosophy, logic, probability, semiotics, artificial intelligence, psychology and history.
Foundations Of Probability Theory
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Author : Himadri Deshpande
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Foundations Of Probability Theory written by Himadri Deshpande and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Science categories.
"Foundations of Probability Theory" offers a thorough exploration of probability theory's principles, methods, and applications. Designed for students, researchers, and practitioners, this comprehensive guide covers both foundational concepts and advanced topics. We begin with basic probability concepts, including sample spaces, events, probability distributions, and random variables, progressing to advanced topics like conditional probability, Bayes' theorem, and stochastic processes. This approach lays a solid foundation for further exploration. Our book balances theory and application, emphasizing practical applications and real-world examples. We cover topics such as statistical inference, estimation, hypothesis testing, Bayesian inference, Markov chains, Monte Carlo methods, and more. Each topic includes clear explanations, illustrative examples, and exercises to reinforce learning. Whether you're a student building a solid understanding of probability theory, a researcher exploring advanced topics, or a practitioner applying probabilistic methods to solve real-world problems, this book is an invaluable resource. We equip readers with the knowledge and tools necessary to tackle complex problems, make informed decisions, and explore probability theory's rich landscape with confidence.
Rule Technologies Foundations Tools And Applications
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Author : Nick Bassiliades
language : en
Publisher: Springer
Release Date : 2015-07-11
Rule Technologies Foundations Tools And Applications written by Nick Bassiliades and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-11 with Computers categories.
This book constitutes the refereed proceedings of the 9th International RuleML Symposium, RuleML 2015, held in Berlin, Germany, in August 2015. The 25 full papers, 4 short papers, 2 full keynote papers, 2 invited research track overview papers, 1 invited paper, 1 invited abstracts presented were carefully reviewed and selected from 63 submissions. The papers cover the following topics: general RuleML track; complex event processing track, existential rules and datalog+/- track; legal rules and reasoning track; rule learning track; industry track.
Foundations Of Intelligent Systems
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Author : Zbigniew W. Ras
language : en
Publisher: Springer Science & Business Media
Release Date : 1996-05-15
Foundations Of Intelligent Systems written by Zbigniew W. Ras 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 1996-05-15 with Computers categories.
This book constitutes the refereed proceedings of the 9th International Symposium on Methodologies for Intelligent Systems, ISMIS '96, held in Zakopane, Poland, in June 1996. The 53 revised full papers presented were selected from a total of 124 submissions; also included are 10 invited papers by leading experts surveying the state of the art in the area. The volume covers the following areas: approximate reasoning, evolutionary computation, intelligent information systems, knowledge representation and integration, learning and knowledge discovery, and AI logics.
Cognitive Foundations Of Agentic Ai From Theory To Practice
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Author : Anand Vemula
language : en
Publisher: Anand Vemula
Release Date :
Cognitive Foundations Of Agentic Ai From Theory To Practice written by Anand Vemula and has been published by Anand Vemula this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Cognitive Foundations of Agentic AI: From Theory to Practice explores the conceptual and technical underpinnings of AI systems that act with autonomy, proactivity, and social intelligence. Drawing from cognitive science, artificial intelligence, and systems theory, this book provides a structured view of how intelligent agents perceive, learn, reason, and interact in dynamic environments. Beginning with a detailed exploration of what defines Agentic AI, the book delves into the cognitive processes that support agency—perception, learning, reasoning, memory, and decision-making. It bridges classical symbolic models with modern deep learning and neuro-symbolic systems to illustrate how hybrid architectures can enable generalizable, goal-driven behavior. Emphasis is placed on modeling real-world complexity, social cognition, and human-like interaction through language, emotional awareness, and theory of mind. The text also critically examines challenges such as generalization, ethical alignment, uncertainty, and explainability. Through illustrative case studies in robotics, healthcare, digital assistants, and multi-agent systems, it highlights the real-world implications and limitations of agentic systems. The final chapters outline practical pathways to building cognitive agents, including architecture design, training environments, and evaluation methods. It encourages a collaborative AI-human future where agents not only support but enhance human decision-making, learning, and creativity. Ideal for AI practitioners, researchers, and graduate students, the book offers both a theoretical framework and practical insights into creating autonomous systems that think, learn, and act intelligently. It invites readers to rethink intelligence not as a fixed trait but as an emergent, contextual process deeply rooted in cognition.
Foundations Of Biomedical Knowledge Representation
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Author : Arjen Hommersom
language : en
Publisher: Springer
Release Date : 2016-01-07
Foundations Of Biomedical Knowledge Representation written by Arjen Hommersom and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-07 with Computers categories.
Medicine and health care are currently faced with a significant rise in their complexity. This is partly due to the progress made during the past three decades in the fundamental biological understanding of the causes of health and disease at the molecular, (sub)cellular, and organ level. Since the end of the 1970s, when knowledge representation and reasoning in the biomedical field became a separate area of research, huge progress has been made in the development of methods and tools that are finally able to impact on the way medicine is being practiced. Even though there are huge differences in the techniques and methods used by biomedical researchers, there is now an increasing tendency to share research results in terms of formal knowledge representation methods, such as ontologies, statistical models, network models, and mathematical models. As there is an urgent need for health-care professionals to make better decisions, computer-based support using this knowledge is now becoming increasingly important. It may also be the only way to integrate research results from the different parts of the spectrum of biomedical and clinical research. The aim of this book is to shed light on developments in knowledge representation at different levels of biomedical application, ranging from human biology to clinical guidelines, and using different techniques, from probability theory and differential equations to logic. The book starts with two introductory chapters followed by 18 contributions organized in the following topical sections: diagnosis of disease; monitoring of health and disease and conformance; assessment of health and personalization; prediction and prognosis of health and disease; treatment of disease; and recommendations.
Bayesian Nets And Causality Philosophical And Computational Foundations
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Author : Jon Williamson
language : en
Publisher: Oxford University Press
Release Date : 2004-12-23
Bayesian Nets And Causality Philosophical And Computational Foundations written by Jon Williamson and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-12-23 with Philosophy categories.
Bayesian nets are widely used in artificial intelligence as a calculus for causal reasoning, enabling machines to make predictions, perform diagnoses, take decisions and even to discover causal relationships. But many philosophers have criticised and ultimately rejected the central assumption on which such work is based - the Causal Markov Condition. So should Bayesian nets be abandoned? What explains their success in artificial intelligence? This book argues that the Causal Markov Condition holds as a default rule: it often holds but may need to be repealed in the face of counterexamples. Thus Bayesian nets are the right tool to use by default but naively applying them can lead to problems. The book develops a systematic account of causal reasoning and shows how Bayesian nets can be coherently employed to automate the reasoning processes of an artificial agent. The resulting framework for causal reasoning involves not only new algorithms but also new conceptual foundations. Probability and causality are treated as mental notions - part of an agent's belief state. Yet probability and causality are also objective - different agents with the same background knowledge ought to adopt the same or similar probabilistic and causal beliefs. This book, aimed at researchers and graduate students in computer science, mathematics and philosophy, provides a general introduction to these philosophical views as well as an exposition of the computational techniques that they motivate.