On The Tweety Penguin Triangle Problem
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On The Tweety Penguin Triangle Problem
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Author : Jean Dezert
language : en
Publisher: Infinite Study
Release Date :
On The Tweety Penguin Triangle Problem written by Jean Dezert and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
In this chapter, one studies the famous well-known and challenging Tweety Penguin Triangle Problem (TPTP or TP2) pointed out by Judea Pearl in one of his books.
Advances And Applications Of Dsmt For Information Fusion Collected Works
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Author : Florentin Smarandache
language : en
Publisher: Infinite Study
Release Date : 2004
Advances And Applications Of Dsmt For Information Fusion Collected Works written by Florentin Smarandache and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.
Papers collected from researchers in fusion information, such as: Florentin Smarandache, Jean Dezert, Hongshe Dang, Chongzhao Han, Frederic Dambreville, Milan Daniel, Mohammad Khoshnevisan, Sukanto Bhattacharya, Albena Tchamova, Tzvetan Semerdjiev, Pavlina Konstantinova, Hongyan Sun, Mohammad Farooq, John J. Sudano, Samuel Corgne, Gregoire Mercier, Laurence Hubert-Moy, Anne-Laure Jousselme, Patrick Maupin and others on Dezert-Smarandache Theory of Plausible and Paradoxical Reasoning (DSmT).. The principal theories available until now for data fusion are the probability theory, the fuzzy set theory, the possibility theory, the hint theory and the theory of evidence. Since last two years J. Dezert and F. Smarandache are actively developing a new theory of plausible and paradoxical reasoning, called DSmT (acronym for Dezert-Smarandache Theory), for information fusion of uncertain and highly conflicting sources of information. The DSmT can be interpreted as a generalization of the Dempster-Shafer Theory (DST) but goes far beyond the DST. The free-DSmT model, which assumes that the ultimate refinement of the frame of discernment of the fusion problem is not accessible due to the intrinsic nature of its elements, is opposite to the Shafer's model (on which is based the DST) assuming the exhaustivity and exclusivity of all elements of the frame of discernment. The DSmT proposes a new theoretical framework for data fusion based on definition of hyper-power sets and a new simple commutative and associative rule of combination. Recently, it has been discovered, through a new DSm hybrid rule of combination, that DSmT can be also extended to problems involving hybrid-models (models including some exclusivity and/or non-existentially constraints). This new important theoretical result offers now to the DSmT a wider class of fusion applications and allows potentially to attack the next generation of complex dynamical/temporal fusion problems. DSmT can also provide a theoretical issue for the fusion of neutrosophic information (extension of fuzzy information proposed by F. Smarandache in nineties - see http://www.gallup.unm.edu/~smarandache/FirstNeutConf.htm for details about the neutrosophy logic and neutrosophy set theory).
Foundations Of Artificial Intelligence And Robotics
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Author : Wendell H. Chun
language : en
Publisher: CRC Press
Release Date : 2024-12-24
Foundations Of Artificial Intelligence And Robotics written by Wendell H. Chun and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-24 with Computers categories.
Artificial intelligence (AI) is a complicated science that combines philosophy, cognitive psychology, neuroscience, mathematics and logic (logicism), economics, computer science, computability, and software. Meanwhile, robotics is an engineering field that compliments AI. There can be situations where AI can function without a robot (e.g., Turing Test) and robotics without AI (e.g., teleoperation), but in many cases, each technology requires each other to exhibit a complete system: having "smart" robots and AI being able to control its interactions (i.e., effectors) with its environment. This book provides a complete history of computing, AI, and robotics from its early development to state‐of‐the‐art technology, providing a roadmap of these complicated and constantly evolving subjects. Divided into two volumes covering the progress of symbolic logic and the explosion in learning/deep learning in natural language and perception, this first volume investigates the coming together of AI (the mind) and robotics (the body), and discusses the state of AI today. Key Features: Provides a complete overview of the topic of AI, starting with philosophy, psychology, neuroscience, and logicism, and extending to the action of the robots and AI needed for a futuristic society Provides a holistic view of AI, and touches on all the misconceptions and tangents to the technologies through taking a systematic approach Provides a glossary of terms, list of notable people, and extensive references Provides the interconnections and history of the progress of technology for over 100 years as both the hardware (Moore’s Law, GPUs) and software, i.e., generative AI, have advanced Intended as a complete reference, this book is useful to undergraduate and postgraduate students of computing, as well as the general reader. It can also be used as a textbook by course convenors. If you only had one book on AI and robotics, this set would be the first reference to acquire and learn about the theory and practice.
Probabilistic Reasoning In Intelligent Systems
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Author : Judea Pearl
language : en
Publisher: Elsevier
Release Date : 2014-06-28
Probabilistic Reasoning In Intelligent Systems written by Judea Pearl and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-28 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.
Advances In Logic Based Intelligent Systems
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Author : Kazumi Nakamatsu
language : en
Publisher: IOS Press
Release Date : 2005
Advances In Logic Based Intelligent Systems written by Kazumi Nakamatsu and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.
LAPTEC' 2005 promoted the discussion and interaction between researchers and practitioners focused on both theoretical and practical disciplines concerning logics applied to technology, with diverse backgrounds including all kinds of intelligent systems having classical or non-classical logics as underlying common matters.
Knowledge Representation And Defeasible Reasoning
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Author : Henry E. Kyburg Jr.
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Knowledge Representation And Defeasible Reasoning written by Henry E. Kyburg Jr. 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.
This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data processing systems of all kinds, no matter whether human, (other) ani mal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psy chology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelli gence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimental, and methodological studies will also ap pear from time to time. The present volume provides a collection of studies that focus on some of the central problems within the domain of artificial intelligence. These difficulties fall into four principal areas: defeasible reasoning (including the frame problem as apart), ordinary language (and the representation prob lems that it generates), the revision of beliefs (and its rules of inference), and knowledge representation (and the logical problems that are encountered there). These papers make original contributions to each of these areas of inquiry and should be of special interest to those who understand the crucial role that is played by questions of logical form. They vividly illustrate the benefits that can emerge from collaborative efforts involving scholars from linguistics, philosophy, computer science, and AI. J. H. F.
Enthymemes And Topoi In Dialogue
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Author : Ellen Breitholtz
language : en
Publisher: Current Research in the Semant
Release Date : 2020-11-19
Enthymemes And Topoi In Dialogue written by Ellen Breitholtz and has been published by Current Research in the Semant this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-19 with Language Arts & Disciplines categories.
"In Enthymemes and Topoi in Dialogue, Ellen Breitholtz presents a novel and precise account of reasoning from an interactional perspective. The account draws on the concepts of enthymemes and topoi, originating in Aristotelian rhetoric and dialectic, and integrates these in a formal dialogue semantic account using TTR, a type theory with records. Argumentation analysis and formal approaches to reasoning often focus the logical validity of arguments on inferences made in discourse from a god's-eye perspective. In contrast, Breitholtz's account emphasises the individual perspectives of interlocutors and the function and acceptability of their reasoning in context. This provides an analysis of interactions where interlocutors have access to different topoi and therefore make different inferences"--
Semantic Networks
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Author : Lokendra Shastri
language : en
Publisher: Pitman Publishing
Release Date : 1988
Semantic Networks written by Lokendra Shastri and has been published by Pitman Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Computers categories.
Shastri’s book describes how a high-level specification of hierarchically structured knowledge about concepts and their properties may be encoded as a massively parallel network of a simple processing elements. The evidential formalization of semantic networks leads to a principled treatment of exceptions, multiple inheritance and conflicting information during inheritance, and the best match or partial match computation during recognition. This formalization offers semantically justifiable solutions to a larger class of problems than existing formulations (e.g. default logic). The network operates without the intervention of a central controller or interpreter. The knowledge as well as mechanisms for drawing limited inferences on it are encoded within the network. It uses controlled spreading activation to solve inheritance and recognition problems in time proportional to the depth of the conceptual hierarchy independent of the total number of concepts in the conceptual structure. The number of nodes in the connectionist network is at most quadratic in the number of concepts. The book has six chapters and one appendix. After the introduction in chapter 1 semantic networks their properties and formalizations are discussed in chapter 2. Especially the significance of inheritance and recognition and the evidential approach to it is pointed out here. Chapter 3 specifies a knowledge representation language. The problems of inheritance and recognition are reformulated in this language. In chapter 4 the evidential formalization and its application to inheritance and recognition are demonstrated. Section 4.1 derives an evidence combination rule. In the following two sections this rule is compared to the DEMPSTER-SHAFER evidence combination rule (section 4.2) and to the BAYES’ rule for computing conditional probabilities. The next two sections develop solutions to evidential inheritance (section 4.4) and evidential recognition (section 4.5) together with constraints for a conceptual structure. The connectionist realization of the memory network is developed in chapter 5. First the need for parallelism is discussed (section 5.1), then the connectionist model (section 5.2) and other massively parallel models of semantic memory (section 5.3) are reviewed. The connectionist encoding of the high-level specification is described in section 5.4 together with the connectivity and computational characteristics of node types. This is followed by examples of network encoding (section 5.5) and the elaboration of some implementation details (section 5.6). In section 5.7 and appendix A there is a proof that the proposed network solves the inheritance and recognition problem in accordance with the evidential formulation and in time proportional to the depth of the conceptual hierarchy. Section 5.8 describes the simulation of the proposed system on a conventional computer together with simulation runs of test examples often cited as being problematic. The book ends with a general discussion (chapter 6).
Ijcai
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Author :
language : en
Publisher:
Release Date : 1995
Ijcai written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Artificial intelligence categories.
Ijcai 95
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Author : Christopher S. Mellish
language : en
Publisher:
Release Date : 1995
Ijcai 95 written by Christopher S. Mellish and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Artificial intelligence categories.