This book proposes a consistent methodology for building intelligent systems. It puts forward several formal models for designing and implementing rules-based systems, and presents illustrative case studies of their applications. These include software engineering, business process systems, Semantic Web, and context-aware systems on mobile devices. Rules offer an intuitive yet powerful method for representing human knowledge, and intelligent systems based on rules have many important applications. However, their practical development requires proper techniques and models - a gap that this book effectively addresses.
Papers direct the focus of interest to the development and use of conceptual models in information systems of various kinds and aim at improving awareness about general or specific problems and solutions in conceptual modelling.
What value does semantic data modeling offer? As an information architect or data science professional, let’s say you have an abundance of the right data and the technology to extract business gold—but you still fail. The reason? Bad data semantics. In this practical and comprehensive field guide, author Panos Alexopoulos takes you on an eye-opening journey through semantic data modeling as applied in the real world. You’ll learn how to master this craft to increase the usability and value of your data and applications. You’ll also explore the pitfalls to avoid and dilemmas to overcome for building high-quality and valuable semantic representations of data. Understand the fundamental concepts, phenomena, and processes related to semantic data modeling Examine the quirks and challenges of semantic data modeling and learn how to effectively leverage the available frameworks and tools Avoid mistakes and bad practices that can undermine your efforts to create good data models Learn about model development dilemmas, including representation, expressiveness and content, development, and governance Organize and execute semantic data initiatives in your organization, tackling technical, strategic, and organizational challenges
This book focuses on recent developments in representational and processing aspects of complex data-intensive applications. Until recently, information systems have been designed around different business functions, such as accounts payable and inventory control. Object-oriented modeling, in contrast, structures systems around the data--the objects--that make up the various business functions. Because information about a particular function is limited to one place--to the object--the system is shielded from the effects of change. Object-oriented modeling also promotes better understanding of requirements, clear designs, and more easily maintainable systems. This book focuses on recent developments in representational and processing aspects of complex data-intensive applications. The chapters cover "hot" topics such as application behavior and consistency, reverse engineering, interoperability and collaboration between objects, and work-flow modeling. Each chapter contains a review of its subject, followed by object-oriented modeling techniques and methodologies that can be applied to real-life applications. Contributors F. Casati, S. Ceri, R. Cicchetti, L. M. L. Delcambre, E. F. Ecklund, D. W. Embley, G. Engels, J. M. Gagnon, R. Godin, M. Gogolla, L. Groenewegen, G. S. Jensen, G. Kappel, B. J. Krämer, S. W. Liddle, R. Missaoui, M. Norrie, M. P. Papazoglou, C. Parent, B. Perniei, P. Poncelet, G. Pozzi, M. Schreft, R. T. Snodgrass, S. Spaccapietra, M. Stumptner, M. Teisseire, W. J. van den Heuevel, S. N. Woodfield
This book is a tribute to Professor Jacek Żurada, who is best known for his contributions to computational intelligence and knowledge-based neurocomputing. It is dedicated to Professor Jacek Żurada, Full Professor at the Computational Intelligence Laboratory, Department of Electrical and Computer Engineering, J.B. Speed School of Engineering, University of Louisville, Kentucky, USA, as a token of appreciation for his scientific and scholarly achievements, and for his longstanding service to many communities, notably the computational intelligence community, in particular neural networks, machine learning, data analyses and data mining, but also the fuzzy logic and evolutionary computation communities, to name but a few. At the same time, the book recognizes and honors Professor Żurada’s dedication and service to many scientific, scholarly and professional societies, especially the IEEE (Institute of Electrical and Electronics Engineers), the world’s largest professional technical professional organization dedicated to advancing science and technology in a broad spectrum of areas and fields. The volume is divided into five major parts, the first of which addresses theoretic, algorithmic and implementation problems related to the intelligent use of data in the sense of how to derive practically useful information and knowledge from data. In turn, Part 2 is devoted to various aspects of neural networks and connectionist systems. Part 3 deals with essential tools and techniques for intelligent technologies in systems modeling and Part 4 focuses on intelligent technologies in decision-making, optimization and control, while Part 5 explores the applications of intelligent technologies.
This book constitutes the refereed proceedings of the 12th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2000, held in Juan-les-Pins, France in October 2000. The 28 revised full papers and six revised short papers presented were carefully reviewed and selected from a high number of high-quality submissions. The book offers topical sections on knowledge modeling languages and tools, ontologies, knowledge acquisition from texts, machine learning, knowledge management and electronic commerce, problem solving methods, knowledge representation, validation, evaluation and certification, and methodologies.
The two-volume set LNAI 7894 and LNCS 7895 constitutes the refereed proceedings of the 12th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2013, held in Zakopane, Poland in June 2013. The 112 revised full papers presented together with one invited paper were carefully reviewed and selected from 274 submissions. The 56 papers included in the second volume are organized in the following topical sections: evolutionary algorithms and their applications; data mining; bioinformatics and medical applications; agent systems, robotics and control; artificial intelligence in modeling and simulation; and various problems of artificial intelligence.
Information technology has now pervaded the legal sector, and the very modern concepts of e-law and e-justice show that automation processes are ubiquitous. European policies on transparency and information society, in particular, require the use of technology and its steady improvement. Some of the revised papers presented in this book originate from a workshop held at the European University Institute of Florence, Italy, in December 2006. The workshop was devoted to the discussion of the different ways of understanding and explaining contemporary law, for the purpose of building computable models of it -- especially models enabling the development of computer applications for the legal domain. During the course of the following year, several new contributions, provided by a number of ongoing (or recently finished) European projects on computation and law, were received, discussed and reviewed to complete the survey. This book presents 20 thoroughly refereed revised papers on the hot topics under research in different EU projects: legislative XML, legal ontologies, semantic web, search and meta-search engines, web services, system architecture, dialectic systems, dialogue games, multi-agent systems (MAS), legal argumentation, legal reasoning, e-justice, and online dispute resolution. The papers are organized in topical sections on knowledge representation, ontologies and XML legislative drafting; knowledge representation, legal ontologies and information retrieval; argumentation and legal reasoning; normative and multi-agent systems; and online dispute resolution.
The definitive presentation of Soar, one AI's most enduring architectures, offering comprehensive descriptions of fundamental aspects and new components. In development for thirty years, Soar is a general cognitive architecture that integrates knowledge-intensive reasoning, reactive execution, hierarchical reasoning, planning, and learning from experience, with the goal of creating a general computational system that has the same cognitive abilities as humans. In contrast, most AI systems are designed to solve only one type of problem, such as playing chess, searching the Internet, or scheduling aircraft departures. Soar is both a software system for agent development and a theory of what computational structures are necessary to support human-level agents. Over the years, both software system and theory have evolved. This book offers the definitive presentation of Soar from theoretical and practical perspectives, providing comprehensive descriptions of fundamental aspects and new components. The current version of Soar features major extensions, adding reinforcement learning, semantic memory, episodic memory, mental imagery, and an appraisal-based model of emotion. This book describes details of Soar's component memories and processes and offers demonstrations of individual components, components working in combination, and real-world applications. Beyond these functional considerations, the book also proposes requirements for general cognitive architectures and explicitly evaluates how well Soar meets those requirements.
This book has its source in the question of whether any knowledge engineering tools can be applied or analyzed in cognition research and what insights and methods of cognitive science might be relevant for knowledge engineers. It presents the proceedings of a workshop organized by the Special Interest Groups Cognition and Knowledge Engineering of the German Society for Informatics, held in February 1992 in Kaiserslautern. The book is structured into three parts. The first part contrasts work in knowledge engineering with approaches from the side of the "soft sciences". The second part deals with case-based approaches in expert systems. Cognition research and the cognitive adequacy of expert systems are discussed in the third part. Contributions from Canada, England, France, Switzerland, and the USA demonstrate how knowledge engineering and cognitive science are woven together internationally.
