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Qualitative Reasoning

Author: Benjamin Kuipers
Publisher: MIT Press
ISBN: 9780262111904
Size: 10.19 MB
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Introduction to qualitative reasoning; Concepts of qualitative simulation; The QSIM representation; Solving qualitative constraints; Dynamic qualitative simulation; Case studies: elementary qualitative models; Comparative statics; Region transitions; Semi-quantitative reasoning; Higher-order derivatives; Global dynamical constraints; Time-scale abstraction; Component-connection models; Compositional modeling; QSIM functions; Creating and debugging a QSIM model; Index.

Computational Discovery Of Scientific Knowledge

Author: Saso Dzeroski
Publisher: Springer Science & Business Media
ISBN: 354073919X
Size: 33.64 MB
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This survey provides an introduction to computational approaches to the discovery of communicable scientific knowledge and details recent advances. It is partly inspired by the contributions of the International Symposium on Computational Discovery of Communicable Knowledge, held in Stanford, CA, USA in March 2001, a number of additional invited contributions provide coverage of recent research in computational discovery.

Recent Advances In Qualitative Physics

Author: Boi Faltings
Publisher: MIT Press
ISBN: 9780262061421
Size: 78.56 MB
Format: PDF, ePub
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These twenty-eight contributions report advances in one of the most active research areas in artificial intellgence. Qualitative modeling techniques are an essential part of building second generation knowledge-based systems. This book provides a timely overview of the field while also giving some indications about applications that appear to be feasible now or in the near future. Chapters are organized into sections covering modeling and simulation, ontologies, computational issues, and qualitative analysis.Modeling a physical system in order to simulate it or solve particular problems regarding the system is an important motivation of qualitative physics, involving formal procedures and concepts. The chapters in the section on modeling address the problem of how to set up and structure qualitative models, particularly for use in simulation. Ontology, or the science of being, is the basis for all modeling. Accordingly, chapters on ontologies discuss problems fundamental for finding representational formalism and inference mechanisms appropriate for different aspects of reasoning about physical systems.Computational issues arising from attempts to turn qualitative theories into practical software are then taken up. In addition to simulation and modeling, qualitative physics can be used to solve particular problems dealing with physical systems, and the concluding chapters present techniques for tasks ranging from the analysis of behavior to conceptual design.Boi Faltings is Associate Professor of Computer Science at the Swiss Federal Institute of Technology, Lausanne. Peter Struss is Head of the Advanced Reasoning Methods Group at Siemens Corporate Research and Development in Munich.

Prolog Programming For Artificial Intelligence

Author: Ivan Bratko
Publisher: Pearson Education
ISBN: 9780201403756
Size: 13.71 MB
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Prolog Programming for Artificial Intelligence Third edition Ivan Bratko The third edition of this best-selling guide to Prolog and Artificial Intelligence has been updated to include key developments in the field while retaining its lucid approach to these topics. Divided into two parts, the first part of the book introduces the programming language Prolog, while the second part teaches Artificial Intelligence using Prolog as a tool for the implementation of AI techniques. Prolog has its roots in logic, however the main aim of this book is to teach Prolog as a practical programming tool. This text therefore concentrates on the art of using the basic mechanisms of Prolog to solve interesting problems. The third edition has been fully revised and extended to provide an even greater range of applications, which further enhance its value as a self-contained guide to Prolog, AI or AI Programming for students and professional programmers alike. Features - Combined approach to Prolog and AI allows flexibility for learning and teaching - Provides a thorough representation of AI, emphasizing practical techniques and Prolog implementations - Prolog programs for use in projects and research are available for download on the World Wide Web. New for this edition: - Constraint Logic Programming - Qualitative Reasoning - Inductive Logic Programming - The addition of belief networks for handling uncertainty - A major update on machine learning - Additional techniques for improving program efficiency - Meta-programming is updated to show how Prolog can be used to implement other languages (including object-oriented programming) - A new Companion Web Site will contain further teaching materials and updates Author: Professor Ivan Bratko leads the AI groups in the Faculty of Computer and Information Science at both Ljubljana University and the Jozef Stefan Institute in Slovenia. He has taught Prolog world-wide as well as applying Prolog in medical expert systems, robot programming, qualitative modelling and computer chess research.

Aaai 92

Author: American Association for Artificial Intelligence (AAAI)
Publisher: AAAI Press
ISBN: 9780262510639
Size: 54.56 MB
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The focus of the AAAI-92 conference is on the re integration of AI as a diverse but coherent whole. Accordingly the traditional list of community-based content areas has been replaced by a more neutral set of taxonomies that span the field. For example, a paper proposing a new epistemology for representing the physical world based on an analysis of human brain structure would be described as "representation, physical world, biological." The papers collected here represent significant research contributions to such areas as the principles underlying cognition, perception, and action in man and machine; the design, application, and evaluation of AI algorithms and systems; and the analysis of domains in which AI systems perform.

Artificial Intelligence Resources In Control And Automation Engineering

Author: Evelio J. González
Publisher: Bentham Science Publishers
ISBN: 1608051269
Size: 60.81 MB
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This e-book focuses on the application of artificial intelligence resources in fields related to Control and Automation Engineering. Techniques such as neural networks, fuzzy logic and expert systems are a key tool for researchers and engineers requiring powerful solutions to a wide range of problems. the e-book should be a useful guide for these engineers and presents practical examples of real cases where these techniques have been successfully applied.