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Blackboard Architectures and Applications focuses on studies done on blackboard architecture in the industries and academe. Particularly given value is the role this paradigm plays in distributed problem solving, parallelism, and intelligent real-time systems. Composed of 21 chapters, the book contains the literature of authors who have diligently conducted studies on this concern. The book starts by discussing the blackboard model of problem solving, including control and organization, wherein goal relationships and their use in blackboard architecture are noted. Also given attention are BBI basic control loop, an empirical comparison of explicit and implicit control architectures, and the dynamic integration of reasoning methods. The book then proceeds with discussions on the concurrency and parallelism of advanced architectures. Taken into consideration include design alternatives for parallel and distributed blackboard systems; the parallelization of blackboard architectures and the Agora system; and a comparison of the cage system and polygon architecture. Real-time blackboard architecture systems are also explored. This part contains experiments, frameworks, and methods designed to approximate processing in real-time problem solving. The text also points at developments in blackboard systems. Given attention are the architecture of ATOME, performance of GBB, the Erasmus system, and the use of blackboard system for distributed problem solving. The book finally focuses on object-oriented blackboard architecture for model-based diagnostic reasoning; dynamic instructional planning in the BB1 architecture; and consideration of blackboard model for cockpit information management. The book is a vital source of data for those wanting to explore the potential of artificial intelligence.
Software architecture is foundational to the development of large, practical software-intensive applications. This brand-new text covers all facets of software architecture and how it serves as the intellectual centerpiece of software development and evolution. Critically, this text focuses on supporting creation of real implemented systems. Hence the text details not only modeling techniques, but design, implementation, deployment, and system adaptation -- as well as a host of other topics -- putting the elements in context and comparing and contrasting them with one another. Rather than focusing on one method, notation, tool, or process, this new text/reference widely surveys software architecture techniques, enabling the instructor and practitioner to choose the right tool for the job at hand. Software Architecture is intended for upper-division undergraduate and graduate courses in software architecture, software design, component-based software engineering, and distributed systems; the text may also be used in introductory as well as advanced software engineering courses.
Object-Oriented Design with Applications has long been the essential reference to object-oriented technology, which, in turn, has evolved to join the mainstream of industrial-strength software development. In this third edition--the first revision in 13 years--readers can learn to apply object-oriented methods using new paradigms such as Java, the Unified Modeling Language (UML) 2.0, and .NET. The authors draw upon their rich and varied experience to offer improved methods for object development and numerous examples that tackle the complex problems faced by software engineers, including systems architecture, data acquisition, cryptoanalysis, control systems, and Web development. They illustrate essential concepts, explain the method, and show successful applications in a variety of fields. You'll also find pragmatic advice on a host of issues, including classification, implementation strategies, and cost-effective project management. New to this new edition are An introduction to the new UML 2.0, from the notation's most fundamental and advanced elements with an emphasis on key changes New domains and contexts A greatly enhanced focus on modeling--as eagerly requested by readers--with five chapters that each delve into one phase of the overall development lifecycle. Fresh approaches to reasoning about complex systems An examination of the conceptual foundation of the widely misunderstood fundamental elements of the object model, such as abstraction, encapsulation, modularity, and hierarchy How to allocate the resources of a team of developers and mange the risks associated with developing complex software systems An appendix on object-oriented programming languages This is the seminal text for anyone who wishes to use object-oriented technology to manage the complexity inherent in many kinds of systems. Sidebars Preface Acknowledgments About the Authors Section I: Concepts Chapter 1: Complexity Chapter 2: The Object Model Chapter 3: Classes and Objects Chapter 4: Classification Section II: Method Chapter 5: Notation Chapter 6: Process Chapter 7: Pragmatics Chapter 8: System Architecture: Satellite-Based Navigation Chapter 9: Control System: Traffic Management Chapter 10: Artificial Intelligence: Cryptanalysis Chapter 11: Data Acquisition: Weather Monitoring Station Chapter 12: Web Application: Vacation Tracking System Appendix A: Object-Oriented Programming Languages Appendix B: Further Reading Notes Glossary Classified Bibliography Index
Taking a learn-by-doing approach, Software Engineering Design: Theory and Practice uses examples, review questions, chapter exercises, and case study assignments to provide students and practitioners with the understanding required to design complex software systems. Explaining the concepts that are immediately relevant to software designers, it be
Computer Architecture/Software Engineering
This unique, accessible textbook gives a comprehensive introduction to software architecture, using ‘clean architecture’ concepts with agile methods and model-driven development. The work introduces the key concepts of software architectures and explains the importance of architectural design for the long-term usefulness and sustainability of software systems. In addition, it describes more than 30 architectural styles and patterns that can be used for constructing mobile applications, enterprise and web applications, machine-learning systems, and safety-critical systems. Topics and features: Combines clean-architecture principles with agile model-driven development Employs practical examples and real industrial cases to illustrate architectures for mobile apps, web apps, enterprise systems, safety-critical systems and machine-learning systems Explores support tools for architectural design and system development using the approach Provides tutorial questions and slides to support teaching and learning Delivers material that has been class-tested over 10 years with more than 1,000 students The textbook can be used to support teaching of an undergraduate module in software architecture, yet also includes more advanced topics suitable for a specialised software architecture module at master’s level. It also will be eminently suitable and relevant for software practitioners and researchers needing or wanting to explore the field in short courses or self-study. Dr. Kevin Lano is Reader in Software Engineering, Department of Informatics, King's College London, UK. Dr. Sobhan Yassipour Tehrani is a Lecturer, Department of Computer Science, University College London, UK.
Uncertainty in Artificial Intelligence: Proceedings of the Eighth Conference (1992) covers the papers presented at the Eighth Conference on Uncertainty in Artificial Intelligence, held at Stanford University on July 17-19, 1992. The book focuses on the processes, methodologies, technologies, and approaches involved in artificial intelligence. The selection first offers information on Relative Evidential Support (RES), modal logics for qualitative possibility and beliefs, and optimizing causal orderings for generating DAGs from data. Discussions focus on reversal, swap, and unclique operators, modal representation of possibility, and beliefs and conditionals. The text then examines structural controllability and observability in influence diagrams, lattice-based graded logic, and dynamic network models for forecasting. The manuscript takes a look at reformulating inference problems through selective conditioning, entropy and belief networks, parallelizing probabilistic inference, and a symbolic approach to reasoning with linguistic quantifiers. The text also ponders on sidestepping the triangulation problem in Bayesian net computations; exploring localization in Bayesian networks for large expert systems; and expressing relational and temporal knowledge in visual probabilistic networks. The selection is a valuable reference for researchers interested in artificial intelligence.
This is the 26th volume in the Encyclopedia of Microcomputers series. It covers topics such as volume graphics and an automatic fuzzy rule generation method for handwriting recognition.