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Aims to provide a forum for genuine interdisciplinary exchange in the spirit of a unified effort towards solving the problems of ontology, with an eye to both theoretical issues and concrete applications. This book contains a range of areas, all of which are important to the development of formal ontologies.

Knowledge representation (Information theory) --- Conceptual structures (Information theory) --- Ontology --- Database design --- Expert systems (Computer science)

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Searching, Bibliographical --- Terms and phrases --- Information retrieval --- Recherche documentaire --- Terminologie --- Recherche de l'information --- Information science --- Information storage and retrieval systems --- Knowledge representation (Information theory) --- Information organization --- terminology --- Traitement de l'information --- Information processing

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This book is about Rational Agents, which can be humans, players in a game, software programs or institutions. Typically, such agents are uncertain about the state of affairs or the state of other agents, and under this partial information they have to decide on which action to take next. This book collects chapters that give formal accounts not only of Uncertainty, Rationality and Agency, but also of their interaction: what are rational criteria to accept certain beliefs, or to modify them; how can degrees of beliefs guide an agent in making decisions; why distinguish between practical and epistemic rationality when agents try to coordinate; what must be common beliefs between agents about each other's rationality in order to act rationally themselves; can an agent assign probabilities to planned actions; how to formalise assumptions about a rational speaker in a conversation obeying Gricean maxims; how should a rational agent best represent the states, consequences, and acts that constitute the agent's rational decision problem? This volume should appeal to researchers addressing issues in artificial systems that have to gather information in order to obtain Knowledge, reason about it and then make a Rational decision about which Action to take next.

Knowledge, Theory of. --- Epistemics. --- Knowledge representation (Information theory) --- Representation of knowledge (Information theory) --- Artificial intelligence --- Information theory --- General semantics --- Knowledge, Theory of --- Epistemology --- Theory of knowledge --- Philosophy --- Psychology --- Artificial intelligence. --- Logic. --- Economic theory. --- Artificial Intelligence. --- Economic Theory/Quantitative Economics/Mathematical Methods. --- Economic theory --- Political economy --- Social sciences --- Economic man --- Argumentation --- Deduction (Logic) --- Deductive logic --- Dialectic (Logic) --- Logic, Deductive --- Intellect --- Science --- Reasoning --- Thought and thinking --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Methodology

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Vagueness is central to the flexibility and robustness of natural language descriptions. Vague concepts are robust to the imprecision of our perceptions, while still allowing us to convey useful, and sometimes vital, information. The study of vagueness in Artificial Intelligence (AI) is therefore motivated by the desire to incorporate this robustness and flexibility into intelligent computer systems. Such a goal, however, requires a formal model of vague concepts that will allow us to quantify and manipulate the uncertainty resulting from their use as a means of passing information between autonomous agents. This volume outlines a formal representation framework for modelling and reasoning with vague concepts in Artificial Intelligence. The new calculus has many applications, especially in automated reasoning, learning, data analysis and information fusion. This book gives a rigorous introduction to label semantics theory, illustrated with many examples, and suggests clear operational interpretations of the proposed measures. It also provides a detailed description of how the theory can be applied in data analysis and information fusion based on a range of benchmark problems.

Computational linguistics. --- Semantics --- Knowledge representation (Information theory) --- Fuzzy sets. --- Fuzzy logic. --- Linguistique informatique --- Sémantique --- Représentation des connaissances --- Ensembles flous --- Logique floue --- Mathematical models. --- Modèles mathématiques --- Artificial intelligence. --- Electronic books. -- local. --- Expert systems (Computer science). --- Uncertainty (Information theory). --- Computational linguistics --- Fuzzy sets --- Fuzzy logic --- Languages & Literatures --- Engineering & Applied Sciences --- Mechanical Engineering --- Computer Science --- Mechanical Engineering - General --- Philology & Linguistics --- Mathematical models --- Information Technology --- Artificial Intelligence --- Knowledge representation (Information theory). --- Uncertainty (Information theory) --- Expert systems (Computer science) --- Models, Mathematical --- Sets, Fuzzy --- Knowledge-based systems (Computer science) --- Systems, Expert (Computer science) --- Measure of uncertainty (Information theory) --- Shannon's measure of uncertainty --- System uncertainty --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Computer science. --- Computers. --- Mathematical statistics. --- Pattern recognition. --- Information theory. --- Complexity, Computational. --- Computer Science. --- Theory of Computation. --- Artificial Intelligence (incl. Robotics). --- Complexity. --- Pattern Recognition. --- Information and Communication, Circuits. --- Probability and Statistics in Computer Science. --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Complexity, Computational --- Communication theory --- Communication --- Cybernetics --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Calculators --- Cyberspace --- Informatics --- Science --- Statistical methods --- Fuzzy mathematics --- Set theory --- Artificial intelligence --- Soft computing --- Information measurement --- Questions and answers --- Engineering. --- Optical pattern recognition. --- Mathematics. --- Artificial Intelligence. --- Math --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Construction --- Industrial arts --- Technology --- Computational complexity. --- Automatic language processing --- Language and languages --- Language data processing --- Linguistics --- Natural language processing (Linguistics) --- Applied linguistics --- Cross-language information retrieval --- Mathematical linguistics --- Multilingual computing --- Nonlinear logic --- Logic, Symbolic and mathematical --- Fuzzy systems --- Representation of knowledge (Information theory) --- Information theory --- Data processing

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th The 14 International Conference on Conceptual Structures (ICCS 2006) was held in Aalborg, Denmark during July 16 – 21, 2006. Responding to the Call for Papers, we received 62 papers from 20 different countries, representing six different continents. This clearly indicates the international nature of the ICCS community as well as the widespread interest which was spawned by the previous conferences. By a thorough review process, 24 papers were selected to be included in this volume. In addition, six invited speakers made contributions which can be found in the first section of this volume. The theme of ICCS 2006––Conceptual Structures: Inspiration and Application–– points to a dual focus of interest that is also reflected in the constellation of papers. From the beginning of the planning of this conference, we focused on inspirational sources that have led to the current state of research in our community, by tracing important historical influences which daily effect work in representing knowledge and in handling representations of conceptual structures. At the same time, we also focused on ways in which these legacies are employed to further advance theory and practice in the field of knowledge representation and processing. With this volume, we believe that a valuable contribution to both aspects of this field is being made. We wish to express our appreciation to all the authors of submitted papers, to the members of the Editorial Board and the Program Committee for all their work and valuable comments.

Conceptual structures (Information theory) --- Graph theory --- Logic diagrams --- Knowledge representation (Information theory) --- Natural language processing (Computer science) --- Structures conceptuelles --- Théorie des graphes --- Logigrammes --- Représentation des connaissances --- Traitement automatique des langues naturelles --- Congresses. --- Congrès --- Computer Science --- Mechanical Engineering - General --- Engineering & Applied Sciences --- Mechanical Engineering --- Information Technology --- Artificial Intelligence --- Diagrams, Logic --- Logic --- Diagrams --- Graphic methods --- Computer science. --- Algorithms. --- Mathematical logic. --- Computer science --- Artificial intelligence. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Discrete Mathematics in Computer Science. --- Mathematical Logic and Formal Languages. --- Algorithm Analysis and Problem Complexity. --- Information Systems Applications (incl. Internet). --- Mathematics. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Computer mathematics --- Discrete mathematics --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Algorism --- Algebra --- Arithmetic --- Informatics --- Science --- Foundations --- Computational complexity. --- Computer software. --- Artificial Intelligence. --- Software, Computer --- Computer systems --- Complexity, Computational --- Computer science—Mathematics. --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software