Knowledge Processing With Interval And Soft Computing

Download Knowledge Processing With Interval And Soft Computing full books in PDF, epub, and Kindle. Read online Knowledge Processing With Interval And Soft Computing ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Knowledge Processing with Interval and Soft Computing

Author : Chenyi Hu
Publisher : Springer Science & Business Media
ISBN 13 : 1848003269
Total Pages : 233 pages
Book Rating : 4.8/5 (48 download)

DOWNLOAD NOW!

Book Synopsis Knowledge Processing with Interval and Soft Computing by : Chenyi Hu

Download or read book Knowledge Processing with Interval and Soft Computing written by Chenyi Hu and published by Springer Science & Business Media. This book was released on 2009-04-03 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interval computing combined with fuzzy logic has become an emerging tool in studying artificial intelligence and knowledge processing (AIKP) applications since it models uncertainties frequently raised in the field. This book provides introductions for both interval and fuzzy computing in a very accessible style. Application algorithms covered in this book include quantitative and qualitative data mining with interval valued datasets, decision making systems with interval valued parameters, interval valued Nash games and interval weighted graphs. Successful applications in studying finance and economics, etc are also included. This book can serve as a handbook or a text for readers interested in applying interval and soft computing for AIKP.

Information Processing and Management of Uncertainty in Knowledge-Based Systems

Author : Marie-Jeanne Lesot
Publisher : Springer Nature
ISBN 13 : 3030501531
Total Pages : 839 pages
Book Rating : 4.0/5 (35 download)

DOWNLOAD NOW!

Book Synopsis Information Processing and Management of Uncertainty in Knowledge-Based Systems by : Marie-Jeanne Lesot

Download or read book Information Processing and Management of Uncertainty in Knowledge-Based Systems written by Marie-Jeanne Lesot and published by Springer Nature. This book was released on 2020-06-05 with total page 839 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtually. The 173 papers were carefully reviewed and selected from 213 submissions. The papers are organized in topical sections: homage to Enrique Ruspini; invited talks; foundations and mathematics; decision making, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied aspects of imprecise probabilities; similarities in artificial intelligence; belief function theory and its applications; aggregation: theory and practice; aggregation: pre-aggregation functions and other generalizations of monotonicity; aggregation: aggregation of different data structures; fuzzy methods in data mining and knowledge discovery; computational intelligence for logistics and transportation problems; fuzzy implication functions; soft methods in statistics and data analysis; image understanding and explainable AI; fuzzy and generalized quantifier theory; mathematical methods towards dealing with uncertainty in applied sciences; statistical image processing and analysis, with applications in neuroimaging; interval uncertainty; discrete models and computational intelligence; current techniques to model, process and describe time series; mathematical fuzzy logic and graded reasoning models; formal concept analysis, rough sets, general operators and related topics; computational intelligence methods in information modelling, representation and processing.

Information Processing and Management of Uncertainty in Knowledge-Based Systems

Author : Davide Ciucci
Publisher : Springer Nature
ISBN 13 : 3031089715
Total Pages : 825 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Information Processing and Management of Uncertainty in Knowledge-Based Systems by : Davide Ciucci

Download or read book Information Processing and Management of Uncertainty in Knowledge-Based Systems written by Davide Ciucci and published by Springer Nature. This book was released on 2022-07-04 with total page 825 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set (CCIS 1601-1602) constitutes the proceedings of the 19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2021, held in Milan, Italy, in July 2022. The 124 papers were carefully reviewed and selected from 188 submissions. The papers are organized in topical sections as follows: aggregation theory beyond the unit interval; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy mathematical analysis and its applications; generalized sets and operators; information fusion techniques based on aggregation functions, pre-aggregation functions, and their generalizations; interval uncertainty; knowledge acquisition, representation and reasoning; logical structures of opposition and logical syllogisms; mathematical fuzzy logics; theoretical and applied aspects of imprecise probabilities; data science and machine learning; decision making modeling and applications; e-health; fuzzy methods in data mining and knowledge discovery; soft computing and artificia intelligence techniques in image processing; soft methods in statistics and data analysis; uncertainty, heterogeneity, reliability and explainability in AI; weak and cautious supervised learning.

Granular, Fuzzy, and Soft Computing

Author : Tsau-Young Lin
Publisher : Springer Nature
ISBN 13 : 1071626280
Total Pages : 936 pages
Book Rating : 4.0/5 (716 download)

DOWNLOAD NOW!

Book Synopsis Granular, Fuzzy, and Soft Computing by : Tsau-Young Lin

Download or read book Granular, Fuzzy, and Soft Computing written by Tsau-Young Lin and published by Springer Nature. This book was released on 2023-03-29 with total page 936 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first edition of the Encyclopedia of Complexity and Systems Science (ECSS, 2009) presented a comprehensive overview of granular computing (GrC) broadly divided into several categories: Granular computing from rough set theory, Granular Computing in Database Theory, Granular Computing in Social Networks, Granular Computing and Fuzzy Set Theory, Grid/Cloud Computing, as well as general issues in granular computing. In 2011, the formal theory of GrC was established, providing an adequate infrastructure to support revolutionary new approaches to computer/data science, including the challenges presented by so-called big data. For this volume of ECSS, Second Edition, many entries have been updated to capture these new developments, together with new chapters on such topics as data clustering, outliers in data mining, qualitative fuzzy sets, and information flow analysis for security applications. Granulations can be seen as a natural and ancient methodology deeply rooted in the human mind. Many daily "things" are routinely granulated into sub "things": The topography of earth is granulated into hills, plateaus, etc., space and time are granulated into infinitesimal granules, and a circle is granulated into polygons of infinitesimal sides. Such granules led to the invention of calculus, topology and non-standard analysis. Formalization of general granulation was difficult but, as shown in this volume, great progress has been made in combing discrete and continuous mathematics under one roof for a broad range of applications in data science.

Black Box Optimization, Machine Learning, and No-Free Lunch Theorems

Author : Panos M. Pardalos
Publisher : Springer Nature
ISBN 13 : 3030665151
Total Pages : 388 pages
Book Rating : 4.0/5 (36 download)

DOWNLOAD NOW!

Book Synopsis Black Box Optimization, Machine Learning, and No-Free Lunch Theorems by : Panos M. Pardalos

Download or read book Black Box Optimization, Machine Learning, and No-Free Lunch Theorems written by Panos M. Pardalos and published by Springer Nature. This book was released on 2021-05-27 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume illustrates the connections between machine learning techniques, black box optimization, and no-free lunch theorems. Each of the thirteen contributions focuses on the commonality and interdisciplinary concepts as well as the fundamentals needed to fully comprehend the impact of individual applications and problems. Current theoretical, algorithmic, and practical methods used are provided to stimulate a new effort towards innovative and efficient solutions. The book is intended for beginners who wish to achieve a broad overview of optimization methods and also for more experienced researchers as well as researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, who will benefit from access to a quick reference to key topics and methods. The coverage ranges from mathematically rigorous methods to heuristic and evolutionary approaches in an attempt to equip the reader with different viewpoints of the same problem.

Fuzzy Information Processing

Author : Guilherme A. Barreto
Publisher : Springer
ISBN 13 : 3319953125
Total Pages : 616 pages
Book Rating : 4.3/5 (199 download)

DOWNLOAD NOW!

Book Synopsis Fuzzy Information Processing by : Guilherme A. Barreto

Download or read book Fuzzy Information Processing written by Guilherme A. Barreto and published by Springer. This book was released on 2018-07-03 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 37th IFSA Conference, NAFIPS 2018, held in Fortaleza, Brazil, in July 2018. The 55 full papers presented were carefully reviewed and selected from 73 submissions. The papers deal with a large spectrum of topics, including theory and applications of fuzzy numbers and sets, fuzzy logic, fuzzy inference systems, fuzzy clustering, fuzzy pattern classification, neuro-fuzzy systems, fuzzy control systems, fuzzy modeling, fuzzy mathematical morphology, fuzzy dynamical systems, time series forecasting, and making decision under uncertainty.

Computing Statistics under Interval and Fuzzy Uncertainty

Author : Hung T. Nguyen
Publisher : Springer
ISBN 13 : 3642249051
Total Pages : 432 pages
Book Rating : 4.6/5 (422 download)

DOWNLOAD NOW!

Book Synopsis Computing Statistics under Interval and Fuzzy Uncertainty by : Hung T. Nguyen

Download or read book Computing Statistics under Interval and Fuzzy Uncertainty written by Hung T. Nguyen and published by Springer. This book was released on 2011-11-17 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: In many practical situations, we are interested in statistics characterizing a population of objects: e.g. in the mean height of people from a certain area. Most algorithms for estimating such statistics assume that the sample values are exact. In practice, sample values come from measurements, and measurements are never absolutely accurate. Sometimes, we know the exact probability distribution of the measurement inaccuracy, but often, we only know the upper bound on this inaccuracy. In this case, we have interval uncertainty: e.g. if the measured value is 1.0, and inaccuracy is bounded by 0.1, then the actual (unknown) value of the quantity can be anywhere between 1.0 - 0.1 = 0.9 and 1.0 + 0.1 = 1.1. In other cases, the values are expert estimates, and we only have fuzzy information about the estimation inaccuracy. This book shows how to compute statistics under such interval and fuzzy uncertainty. The resulting methods are applied to computer science (optimal scheduling of different processors), to information technology (maintaining privacy), to computer engineering (design of computer chips), and to data processing in geosciences, radar imaging, and structural mechanics.

Concepts of Soft Computing

Author : Snehashish Chakraverty
Publisher : Springer
ISBN 13 : 9811374309
Total Pages : 195 pages
Book Rating : 4.8/5 (113 download)

DOWNLOAD NOW!

Book Synopsis Concepts of Soft Computing by : Snehashish Chakraverty

Download or read book Concepts of Soft Computing written by Snehashish Chakraverty and published by Springer. This book was released on 2019-04-30 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses soft computing, which provides an efficient platform to deal with imprecision, uncertainty, vagueness and approximation in order to attain robustness and reliable computing. It explores two major concepts of soft computing: fuzzy set theory and neural networks, which relate to uncertainty handling and machine learning techniques respectively. Generally, fuzzy sets are considered as vague or uncertain sets having membership function lying between 0 and 1, and ANN is a type of artificial intelligence that attempts to imitate the way a human brain works by configuring specific applications, for instance pattern recognition or data classification, through learning processes. The book also presents C/MATLAB programming codes related to the basics of fuzzy set, interval arithmetic and ANN in a concise, practical and adaptable manner along, with simple examples and self-validation unsolved practice questions in few cases

Explainable AI and Other Applications of Fuzzy Techniques

Author : Julia Rayz
Publisher : Springer Nature
ISBN 13 : 3030820998
Total Pages : 506 pages
Book Rating : 4.0/5 (38 download)

DOWNLOAD NOW!

Book Synopsis Explainable AI and Other Applications of Fuzzy Techniques by : Julia Rayz

Download or read book Explainable AI and Other Applications of Fuzzy Techniques written by Julia Rayz and published by Springer Nature. This book was released on 2021-07-27 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on an overview of the AI techniques, their foundations, their applications, and remaining challenges and open problems. Many artificial intelligence (AI) techniques do not explain their recommendations. Providing natural-language explanations for numerical AI recommendations is one of the main challenges of modern AI. To provide such explanations, a natural idea is to use techniques specifically designed to relate numerical recommendations and natural-language descriptions, namely fuzzy techniques. This book is of interest to practitioners who want to use fuzzy techniques to make AI applications explainable, to researchers who may want to extend the ideas from these papers to new application areas, and to graduate students who are interested in the state-of-the-art of fuzzy techniques and of explainable AI—in short, to anyone who is interested in problems involving fuzziness and AI in general.

Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications

Author : Andrew Pownuk
Publisher : Springer
ISBN 13 : 3319910264
Total Pages : 202 pages
Book Rating : 4.3/5 (199 download)

DOWNLOAD NOW!

Book Synopsis Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications by : Andrew Pownuk

Download or read book Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications written by Andrew Pownuk and published by Springer. This book was released on 2018-05-03 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at such solutions, as well as case studies demonstrating how these theoretical ideas can be translated into practical applications in the geosciences, pavement engineering, etc. In all these developments, the authors’ objectives were to provide accurate estimates of the resulting uncertainty; to offer solutions that require reasonably short computation times; to offer content that is accessible for engineers; and to be sufficiently general - so that readers can use the book for many different problems. The authors also describe how to make decisions under different types of uncertainty. The book offers a valuable resource for all practical engineers interested in better ways of gauging uncertainty, for students eager to learn and apply the new techniques, and for researchers interested in processing heterogeneous uncertainty.

Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications

Author : Jesús Medina
Publisher : Springer
ISBN 13 : 3319914790
Total Pages : 773 pages
Book Rating : 4.3/5 (199 download)

DOWNLOAD NOW!

Book Synopsis Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications by : Jesús Medina

Download or read book Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications written by Jesús Medina and published by Springer. This book was released on 2018-05-29 with total page 773 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).

Models and Methods for Interval-Valued Cooperative Games in Economic Management

Author : Deng-Feng Li
Publisher : Springer
ISBN 13 : 3319289985
Total Pages : 137 pages
Book Rating : 4.3/5 (192 download)

DOWNLOAD NOW!

Book Synopsis Models and Methods for Interval-Valued Cooperative Games in Economic Management by : Deng-Feng Li

Download or read book Models and Methods for Interval-Valued Cooperative Games in Economic Management written by Deng-Feng Li and published by Springer. This book was released on 2016-02-02 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes several commonly used interval-valued solution concepts of interval-valued cooperative games with transferable utility. It thoroughly investigates these solutions, thereby establishing the properties, models, methods, and applications. The first chapter proposes the interval-valued least square solutions and quadratic programming models, methods, and properties. Next, the satisfactory-degree-based non-linear programming models for computing interval-valued cores and corresponding bisection algorithm are explained. Finally, the book explores several simplification methods of interval-valued solutions: the interval-valued equal division and equal surplus division values; the interval-valued Shapley, egalitarian Shapley, and discounted Shapley values; the interval-valued solidarity and generalized solidarity values; and the interval-valued Banzhaf value. This book is designed for individuals from different fields and disciplines, such as decision science, game theory, management science, operations research, fuzzy sets or fuzzy mathematics, applied mathematics, industrial engineering, finance, applied economics, expert system, and social economy as well as artificial intelligence. Moreover, it is suitable for teachers, postgraduates, and researchers from different disciplines: decision analysis, management, operations research, fuzzy mathematics, fuzzy system analysis, applied mathematics, systems engineering, project management, supply chain management, industrial engineering, applied economics, and hydrology and water resources.

Modeling Invasive Alien Plant Species

Author : H.O.W. Peiris
Publisher : CRC Press
ISBN 13 : 1000421902
Total Pages : 209 pages
Book Rating : 4.0/5 (4 download)

DOWNLOAD NOW!

Book Synopsis Modeling Invasive Alien Plant Species by : H.O.W. Peiris

Download or read book Modeling Invasive Alien Plant Species written by H.O.W. Peiris and published by CRC Press. This book was released on 2021-08-23 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modelling Invasive Alien Plant Species: Fuzzy Based Uncertainty presents the application of different fuzzy set theory techniques in developing risk assessment models for invasive plant species- those whose introduction and spread outside their natural range threatens local biodiversity. Invasion risk of species is expressed by biological traits which would be considered as the risk factors accompanied with uncertainty and imprecision. The book considers both quantitative and qualitative inputs in modelling the invasive risk by incorporating different mathematical models based on fuzzy set theory operators, interval methods, and fuzzy linguistic operators. The proposed models can be applied for investigating risk of invasive alien plant species in various regions and conditions. Features: Uniquely merges mathematical models with biological expressions. Presents different factor-based models as a case study on the risk of invasive alien plant species. Explains how users can perform primary-level risk assessment through fuzzy modeling techniques. Appropriate for upper-level students, researchers, and practicing professionals, this book shows how conventional approaches such as probability theory can be of limited use to solve issues of uncertainty, and how they fuzzy set theory plays a better role in understanding uncertain system dynamics, such invasive plant modelling.

A New Paradigm of Knowledge Engineering by Soft Computing

Author : Liya Ding
Publisher : World Scientific
ISBN 13 : 9789812794604
Total Pages : 396 pages
Book Rating : 4.7/5 (946 download)

DOWNLOAD NOW!

Book Synopsis A New Paradigm of Knowledge Engineering by Soft Computing by : Liya Ding

Download or read book A New Paradigm of Knowledge Engineering by Soft Computing written by Liya Ding and published by World Scientific. This book was released on 2001 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soft computing (SC) consists of several computing paradigms, including neural networks, fuzzy set theory, approximate reasoning, and derivative-free optimization methods such as genetic algorithms. The integration of those constituent methodologies forms the core of SC. In addition, the synergy allows SC to incorporate human knowledge effectively, deal with imprecision and uncertainty, and learn to adapt to unknown or changing environments for better performance. Together with other modern technologies, SC and its applications exert unprecedented influence on intelligent systems that mimic human intelligence in thinking, learning, reasoning, and many other aspects. Knowledge engineering (KE), which deals with knowledge acquisition, representation, validation, inferencing, explanation, and maintenance, has made significant progress recently, owing to the indefatigable efforts of researchers. Undoubtedly, the hot topics of data mining and knowledge/data discovery have injected new life into the classical AI world. This book tells readers how KE has been influenced and extended by SC and how SC will be helpful in pushing the frontier of KE further. It is intended for researchers and graduate students to use as a reference in the study of knowledge engineering and intelligent systems. The reader is expected to have a basic knowledge of fuzzy logic, neural networks, genetic algorithms, and knowledge-based systems. Contents: Knowledge Engineering and Soft Computing OCo An Introduction (L-Y Ding); Fuzzy Knowledge-Based Systems: Linguistic Integrity: A Framework for Fuzzy Modeling OCo AFRELI Algorithm (J Espinosa & J Vandewalle); A New Approach to Acquisition of Comprehensible Fuzzy Rules (H Ohno & T Furuhashi); Fuzzy Rule Generation with Fuzzy Singleton-Type Reasoning Method (Y Shi & M Mizumoto); Antecedent Validity Adaptation Principle for Table Look-Up Scheme (P-T Chan & A B Rad); Fuzzy Spline Interpolation in Sparse Fuzzy Rule Bases (M F Kawaguchi & M Miyakoshi); Revision Principle Applied for Approximate Reasoning (L-Y Ding et al.); Handling Null Queries with Compound Fuzzy Attributes (S-L Wang & Y-J Tsai); Fuzzy System Description Language (K Otsuka et al.); Knowledge Representation, Integration, and Discovery by Soft Computing: Knowledge Representation and Similarity Measure in Learning a Vague Legal Concept (M Q Xu et al.); Trend Fuzzy Sets and Recurrent Fuzzy Rules for Ordered Dataset Modelling (J F Baldwin et al.); Approaches to the Design of Classification Systems from Numerical Data and Linguistic Knowledge (H Ishibuchi et al.); A Clustering Based on Self-Organizing Map and Knowledge Discovery by Neural Network (K Nakagawa et al.); Probabilistic Rough Induction (J-Z Dong et al.); Data Mining via Linguistic Summaries of Databases: An Interactive Approach (J Kacprzyk & S Zadrozny); and other papers. Readership: Graduate students, researchers and lecturers in knowledge engineering and soft computing."

Interval / Probabilistic Uncertainty and Non-classical Logics

Author : Van-Nam Huynh
Publisher : Springer Science & Business Media
ISBN 13 : 3540776648
Total Pages : 376 pages
Book Rating : 4.5/5 (47 download)

DOWNLOAD NOW!

Book Synopsis Interval / Probabilistic Uncertainty and Non-classical Logics by : Van-Nam Huynh

Download or read book Interval / Probabilistic Uncertainty and Non-classical Logics written by Van-Nam Huynh and published by Springer Science & Business Media. This book was released on 2008-01-11 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the proceedings of the first International Workshop on Interval/Probabilistic Uncertainty and Non Classical Logics, Ishikawa, Japan, March 25-28, 2008. The workshop brought together researchers working on interval and probabilistic uncertainty and on non-classical logics. It is hoped this workshop will lead to a boost in the much-needed collaboration between the uncertainty analysis and non-classical logic communities, and thus, to better processing of uncertainty.

Intelligent Autonomous Systems

Author : Dilip Kumar Pratihar
Publisher : Springer
ISBN 13 : 3642116760
Total Pages : 266 pages
Book Rating : 4.6/5 (421 download)

DOWNLOAD NOW!

Book Synopsis Intelligent Autonomous Systems by : Dilip Kumar Pratihar

Download or read book Intelligent Autonomous Systems written by Dilip Kumar Pratihar and published by Springer. This book was released on 2010-03-11 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Autonomous Systems (IAS) are the physical embodiment of machine intelligence providing a core concept for integrating various advanced techno- gies with pattern recognition and learning. The basic philosophy of IAS research is to explore and understand the nature of intelligence in problems of perception, reasoning, learning and control in order to develop and implement the theory to engineered realization. In other words, the objective is to formulate various me- odologies for the development of robots which can operate autonomously and exhibit intelligent behavior by making appropriate decisions to perform the right task at the right time. Since IAS basically deals with the integration of machines, computing, sensing, and software to create intelligent systems capable of intera- ing with the complexities of the real world, advanced topics like soft computing, artificial life, evolutionary biology, and cognitive psychology have great promise in improving its intelligence and performance. Because of the inter-disciplinary character, the subject has several challenging issues for research, design and development covering a number of disciplines. These issues are further concerned with the development of both technology and methodology apart from various operations. The present research monograph titled “Intelligent Autonomous Systems: Foundations and Applications", edited by two renowned researchers, Professor Dilip K. Pratihar of IIT, Kharagpur, India and Professor Lakhmi C. Jain, Univ- sity of South Australia, Australia, provides a fairly representative cross-section of the activities that is going on all over the world in this area.

Management of Knowledge Imperfection in Building Intelligent Systems

Author : Eugene Roventa
Publisher : Springer Science & Business Media
ISBN 13 : 3540774629
Total Pages : 263 pages
Book Rating : 4.5/5 (47 download)

DOWNLOAD NOW!

Book Synopsis Management of Knowledge Imperfection in Building Intelligent Systems by : Eugene Roventa

Download or read book Management of Knowledge Imperfection in Building Intelligent Systems written by Eugene Roventa and published by Springer Science & Business Media. This book was released on 2008-10-14 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many good AI books. Usually they consecrate at most one or two chapters to the imprecision knowledge processing. To our knowledge this is among the few books to be entirely dedicated to the treatment of knowledge imperfection when bui- ing intelligent systems. We consider that an entire book should be focused on this important aspect of knowledge processing. The expected audience for this book - cludes undergraduate students in computer science, IT&C, mathematics, business, medicine, etc. , graduates, specialists and researchers in these fields. The subjects treated in the book include expert systems, knowledge representation, reasoning under knowledge Imperfection (Probability Theory, Possibility Theory, Belief Theory, and Approximate Reasoning). Most of the examples discussed in details throughout the book are from the medical domain. Each chapter ends with a set of carefully pe- gogically chosen exercises, which complete solution provided. Their understanding will trigger the comprehension of the theoretical notions, concepts and results. Chapter 1 is dedicated to the review of expert systems. Hence are briefly discussed production rules, structure of ES, reasoning in an ES, and conflict resolution. Chapter 2 treats knowledge representation. That includes the study of the differences between data, information and knowledge, logical systems with focus on predicate calculus, inference rules in classical logic, semantic nets and frames.