Intelligent systems are necessary to handle modern computer-based technologies managing information and knowledge. This book discusses the theories required to help provide solutions to difficult problems in the construction of intelligent systems. Particular attention is paid to situations in which the available information and data may be imprecise, uncertain, incomplete or of a linguistic nature. The main aspects of clustering, classification, summarization, decision making and systems modeling are also addressed. Topics covered in the book include fundamental issues in uncertainty, the rapidly emerging discipline of information aggregation, neural networks, Bayesian networks and other network methods, as well as logic-based systems.
As its title suggests, "Uncertainty Management in Information Systems" is a book about how information systems can be made to manage information permeated with uncertainty. This subject is at the intersection of two areas of knowledge: information systems is an area that concentrates on the design of practical systems that can store and retrieve information; uncertainty modeling is an area in artificial intelligence concerned with accurate representation of uncertain information and with inference and decision-making under conditions infused with uncertainty. New applications of information systems require stronger capabilities in the area of uncertainty management. Our hope is that lasting interaction between these two areas would facilitate a new generation of information systems that will be capable of servicing these applications. Although there are researchers in information systems who have addressed themselves to issues of uncertainty, as well as researchers in uncertainty modeling who have considered the pragmatic demands and constraints of information systems, to a large extent there has been only limited interaction between these two areas. As the subtitle, "From Needs to Solutions," indicates, this book presents view points of information systems experts on the needs that challenge the uncer tainty capabilities of present information systems, and it provides a forum to researchers in uncertainty modeling to describe models and systems that can address these needs.
This book describes the latest advances in intelligent techniques such as fuzzy logic, neural networks, and optimization algorithms, and their relevance in building intelligent information systems in combination with applied mathematics. The authors also outline the applications of these systems in areas like intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and optimization of complex problems. By sharing fresh ideas and identifying new targets/problems it offers young researchers and students new directions for their future research. The book is intended for readers from mathematics and computer science, in particular professors and students working on theory and applications of intelligent systems for real-world applications.
This book constitutes the refereed proceedings of the 18th International Conference on Mobile Web and Intelligent Information Systems, MobiWIS 2022, held in Rome, Italy, in August 2022.The 18 full papers and 1 short paper presented in this book were carefully reviewed and selected from 51 submissions. The papers of MobiWIS 2022 deal focus on topics such as security and privacy; web and mobile applications; networking and communication; intelligent information systems; and IoT and ubiquitous computing.
This book constitutes the thoroughly refereed proceedings of the CAiSE Forum 2023 which was held in Zaragoza, Spain, in June 2023, as part of the 35th International Conference on Advanced Information Systems Engineering, CAiSE 2023. The CAiSE Forum is a place within the CAiSE conference for presenting and discussing new ideas and tools related to information systems engineering. Intended to serve as an interactive platform, the Forum aims at the presentation of emerging new topics and controversial positions, as well as demonstration of innovative systems, tools and applications. This year’s edition of the conference put a special emphasis on the theme of Cyber-Human Systems. A total of 25 papers was sent for peer review. 12 of these papers were invited from CAiSE and 13 have been directly submitted to the Forum. After a careful review and selection, 12 of the invited and 6 of the newly submitted papers have been accepted for publication.
This volume contains articles accepted for presentation during The Intelligent Information Systems Symposium I1S'2000 which was held in Bystra, Poland, on June 12-16, 2000. This is ninth, in the order, symposium organized by the Institute of Computer Science of Polish Academy of Sciences and devoted to new trends in (broadly understood) Artificial Intelligence. The idea of organizing such meetings dates back to 1992. Our main in tention guided the first, rather small-audience, workshop in the series was to resume the results gained in Polish scientific centers as well as contrast them with the research performed by Polish scientists working at the uni versities in Europe and USA. This idea proved to be attractive enough that we decided to continue such meetings. As the years went by, the workshops has transformed into regular symposia devoted to such fields like Machine Learning, Knowledge Discovery, Natural Language Processing, Knowledge Based Systems and Reasoning, and Soft Computing (Le. Fuzzy and Rough Sets, Bayesian Networks, Neural Networks and Evolutionary Algorithms). At present, about 50 papers prepared by researches from Poland and other countries are usually presented. Besides, for several years now, the symposia are accompanied by a number of tutorials, given by the outstanding scientists in their domain. Up to this year the proceedings were published as our local publication and they were distributed among the scientific libraries. We feel however, that the subject matter as well as the quality of papers is sufficient to present the proceedings to a broader scientific audience.
The Software Engineering and Knowledgebase Systems (SOFfEKS) Research Group of the Department of Computer Science, Concordia University, Canada, organized a workshop on Incompleteness and Uncertainty in Information Systems from October 8-9, 1993 in Montreal. A major aim of the workshop was to bring together researchers who share a concern for issues of incompleteness and uncertainty. The workshop attracted people doing fundamental research and industry oriented research in databases, software engineering and AI from North America, Europe and Asia. The workshop program featured six invited talks and twenty other presentations. The invited speakers were: Martin Feather (University of Southern CalifornialInformation Systems Institute) Laks V. S. Lakshmanan (Concordia University) Ewa Orlowska (Polish Academy of Sciences) z. Pawlak (Warsaw Technical University and Academy of Sciences) F. Sadri (Concordia University) A. Skowron (Warsaw University) The papers can be classified into four groups: rough sets and logic, concept analysis, databases and information retrieval, and software engineering. The workshop opened with a warm welcome speech from Dr. Dan Taddeo, Dean, Faculty of Engineering and Computer Science. The first day's presentations were in rough sets, databases and information retrieval. Papers given on the second day centered around software engineering and concept analysis. Sufficient time was given in between presentations to promote active interactions and numerous lively discussions. At the end of two days, the participants expressed their hope that this workshop would be continued.
The third edition of this bestseller examines the principles of artificial intelligence and their application to engineering and science, as well as techniques for developing intelligent systems to solve practical problems. Covering the full spectrum of intelligent systems techniques, it incorporates knowledge-based systems, computational intelligence, and their hybrids. Using clear and concise language, Intelligent Systems for Engineers and Scientists, Third Edition features updates and improvements throughout all chapters. It includes expanded and separated chapters on genetic algorithms and single-candidate optimization techniques, while the chapter on neural networks now covers spiking networks and a range of recurrent networks. The book also provides extended coverage of fuzzy logic, including type-2 and fuzzy control systems. Example programs using rules and uncertainty are presented in an industry-standard format, so that you can run them yourself. The first part of the book describes key techniques of artificial intelligence—including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), frames, objects, agents, symbolic learning, case-based reasoning, genetic algorithms, optimization algorithms, neural networks, hybrids, and the Lisp and Prolog languages. The second part describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. The author provides sufficient detail to help you develop your own intelligent systems for real applications. Whether you are building intelligent systems or you simply want to know more about them, this book provides you with detailed and up-to-date guidance. Check out the significantly expanded set of free web-based resources that support the book at: http://www.adrianhopgood.com/aitoolkit/
