الصفحة 8
الصفحة 8
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Advances in Artificial Intelligence - IBERAMIA 2008 ; 11th Ibero-American Conference on AI, Lisbon, Portugal, October 14-17, 2008. Proceedings

Constitutes the refereed proceedings of the 11th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2008, held in Lisbon, Portugal, in October 2008.

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Advances in Applied Artificial Intelligence ; 19th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2006, Annecy, France, June 27-30, 2006, Proceedings

Intelligent Design and complex problem solving are twined like wife and husband.” In the current competitive global industrial environment there are many pr- lems which need intelligent systems technology for optimal solutions. The central theme of the 19th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2006) is to focus on the research methodologies and practical implementations of these methodologies for intelligent solutions of problems in real-world applications. We are pleased to present the papers in these proceedings which cover va- ous aspects of applications of applied intelligent systems. We received more than 330 papers from many countries and each paper was reviewed by at least two reviewers. Only 134 papers were selected for presentation in the normal and special sessions.

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Advanced methods for knowledge discovery from complex data

An overview of the field, looking at the issues and challenges involved is followed by coverage of recent trends in data mining, including descriptions of some currently popular tools like genetic algorithms, neural networks and case-based reasoning. This provides the context for the subsequent chapters on methods and applications. Part I is devoted to the foundations of mining different types of complex data like trees, graphs, links and sequences. A knowledge discovery approach based on problem decomposition is also described. Part II presents important applications of advanced mining techniques to data in unconventional and complex domains, such as life sciences, world-wide web, image databases, cyber security and sensor networks. With a good balance of introductory material on the knowledge discovery process, advanced issues and state-of-the-art tools and techniques, as well as recent working applications this book provides a representative selection of the available methods and their evaluation in real domains. It will be useful to students at Masters and PhD level in Computer Science, as well as practitioners in the field.

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Adaptive Autonomous Secure Cyber Systems

Establishes scientific foundations for adaptive autonomous cyber systems and ultimately brings about a more secure and reliable Internet. The recent advances in adaptive cyber defense (ACD) have developed a range of new ACD techniques and methodologies for reasoning in an adaptive environment.

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Abstraction, Reformulation, and Approximation ; 7th International Symposium, SARA 2007, Whistler, Canada, July 18-21, 2007, Proceedings

This volume contains the proceedings of SARA 2007, the seventh symposium, held at Whistler Village, British Columbia, Canada, July 18-21. Three distinguished speakers were invited to give keynote presentations, and their abstracts are included herein,It has been recognized since the inception of artificial intelligence that abstractions, problem reformulations and approximations (AR&A) are central to human common-sense reasoning and problem solving and to the ability of systems to reason effectively in complex domains.AR&A techniques have been used in a variety of problem-solving settings, including automated reasoning, cognitive modelling.

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Abstraction, reformulation and approximation ; 6th International symposium, SARA 2005, Airth Castle, Scotland, UK, July 26-29, 2005, proceedings

This volume contains the proceedings of the 6th Symposium on Abstraction, Reformulation and Approximation (SARA 2005). the proceedings have been published in the LNAI series of Springer. Abstractions, reformulations and approximations (AR&A) have found app- cationsin avarietyofdisciplines andproblems, including constraintsatisfaction, design, diagnosis, machine learning, planning, qualitative reasoning, scheduling, resource allocation and theorem proving, but are also deeply rooted in philo- phy and cognitive science. The papers in this volume capture a cross-section of the various facets of the ?eld and of its applications. One of the primary uses of AR&A is oriented to overcome computational intractability. AR&A techniques, however, have also proved useful for knowledge acquisition, explanation and other applications.

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Abstraction, refinement and proof for probabilistic systems

Probabilistic techniques are increasingly being employed in computer programs and systems because they can increase efficiency in sequential algorithms, enable otherwise nonfunctional distribution applications, and allow quantification of risk and safety in general. This makes operational models of how they work, and logics for reasoning about them, extremely important. Abstraction, Refinement and Proof for Probabilistic Systems presents a rigorous approach to modeling and reasoning about computer systems that incorporate probability. Its foundations lie in traditional Boolean sequential-program logic—but its extension to numeric rather than merely true-or-false judgments takes it much further, into areas such as randomized algorithms, fault tolerance, and, in distributed systems, almost-certain symmetry breaking. The presentation begins with the familiar "assertional" style of program development and continues with increasing specialization: Part I treats probabilistic program logic, including many examples and case studies; Part II sets out the detailed semantics; and Part III applies the approach to advanced material on temporal calculi and two-player games.

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A General introduction to data analytics

A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming. A guide to the reasoning behind data mining techniques. A unique illustrative example that extends throughout all the chapters. Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts

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