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Record Nr. |
UNINA9910143919503321 |
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Titolo |
New Frontiers in Artificial Intelligence : Joint JSAI 2001 Workshop Post-Proceedings / / edited by Takao Terano, Toyoaki Nishida, Akira Namatame, Syrusaku Tsumoto, Yukio Ohsawa, Takashi Washio |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 |
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ISBN |
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Edizione |
[1st ed. 2001.] |
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Descrizione fisica |
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1 online resource (XXVIII, 556 p.) |
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Collana |
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Lecture Notes in Artificial Intelligence ; ; 2253 |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Robotics |
Automation |
Computer engineering |
Information storage and retrieval |
Application software |
User interfaces (Computer systems) |
Artificial Intelligence |
Robotics and Automation |
Computer Engineering |
Information Storage and Retrieval |
Information Systems Applications (incl. Internet) |
User Interfaces and Human Computer Interaction |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters and index. |
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Nota di contenuto |
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Social Intelligence Design -- Social Intelligence Design — An Overview -- FaintPop: In Touch with the Social Relationships -- From Virtual Environment to Virtual Community -- Collaborative Innovation Tools -- Bricks & Bits & Interaction -- A Distributed Multi-agent System for the Self-Evaluation of Dialogs -- Public Opinion Channel: A System for Augmenting Social Intelligence of a Community -- Enabling Public Discourse -- Internet, Discourses, and Democracy -- How to Evaluate |
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Social Intelligence Design -- Agent-Based Approaches in Economic and Social Complex Systems -- Overview -- Analyzing Norm Emergence in Communal Sharing via Agent-Based Simulation -- Toward Cumulative Progress in Agent-Based Simulation -- Complexity of Agents and Complexity of Markets -- U-Mart Project: Learning Economic Principles from the Bottom by Both Human and Software Agents -- A Multi-objective Genetic Algorithm Approach to Construction of Trading Agents for Artificial Market Study -- Agent-Based Simulation for Economic and Environmental Studies -- Avatamsaka Game Experiment as a Nonlinear Polya Urn Process -- Effects of Punishment into Actions in Social Agents -- Analysis of Norms Game with Mutual Choice -- Cooperative Co-evolution of Multi-agents -- Social Interaction as Knowledge Trading Games -- World Trade League as a Standard Problem for Multi-agent Economics — Concept and Background -- Virtual Economy Simulation and Gaming — An Agent Based Approach — -- Boxed Economy Foundation Model: Model Framework for Agent-Based Economic Simulations -- Rough Set Theory and Granular Computing -- Workshop on Rough Set Theory and Granular Computing — Summary -- Bayes’ Theorem Revised — The Rough Set View -- Toward Intelligent Systems: Calculi of Information Granules -- Soft Computing Pattern Recognition: Principles, Integrations, and Data Mining -- Identifying Upper and Lower Possibility Distributions with Rough Set Concept -- On Fractals in Information Systems: The First Step -- Generalizations of Fuzzy Multisets for Including Infiniteness -- Fuzzy c-Means and Mixture Distribution Model for Clustering Based on L 1 – Space -- On Rough Sets under Generalized Equivalence Relations -- Two Procedures for Dependencies among Attributes in a Table with Non-deterministic Information: A Summary -- An Application of Extended Simulated Annealing Algorithm to Generate the Learning Data Set for Speech Recognition System -- Generalization of Rough Sets with ?-Coverings of the Universe Induced by Conditional Probability Relations -- On Mining Ordering Rules -- Non-additive Measures by Interval Probability Functions -- Susceptibility to Consensus of Conflict Profiles -- Analysis of Image Sequences for the Unmanned Aerial Vehicle -- The Variable Precision Rough Set Inductive Logic Programming Model and Web Usage Graphs -- Optimistic Priority Weights with an Interval Comparison Matrix -- Rough Set Theory in Conflict Analysis -- Dealing with Imperfect Data by RS-ILP -- Extracting Patterns Using Information Granules: A Brief Introduction -- Classification Models Based on Approximate Bayesian Networks -- Identifying Adaptable Components — A Rough Sets Style Approach -- Rough Measures and Integrals: A Brief Introduction -- Association Rules in Semantically Rich Relations: Granular Computing Approach -- A Note on Filtration and Granular Reasoning -- A Note on Conditional Logic and Association Rules -- Analysis of Self-Injurious Behavior by the LERS Data Mining System -- A Clustering Method for Nominal and Numerical Data Based on Rough Set Theory -- A Design of Architecture for Rough Set Processor -- Chance Discovery -- The Scope of Chance Discovery -- Chance Discovery Using Dialectical Argumentation -- Methodological Considerations on Chance Discovery -- Future Directions of Communities on the Web -- A Document as a Small World -- Support System for Creative Activity by Information Acquirement through Internet -- An Approach to Support Long-Term Creative Thinking and Its Feasibility -- Chance Discovery by Creative Communicators Observed in Real Shopping Behavior -- The Role of Counterexamples in Discovery Learning Environment: Awareness of the Chance for Learning -- Integrating Data Mining Techniques and Design Information Management for Failure Prevention -- Action Proposal as |
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Discovery of Context -- Retrieval of Similar Time-Series Patterns for Chance Discovery -- Fuzzy Knowledge Based Systems and Chance Discovery -- Challenge in Knowledge Discovery and Datamining -- JSAI KDD Challenge 2001: JKDD01 -- Knowledge Discovery Support from a Meningoencephalitis Dataset Using an Automatic Composition Tool for Inductive Applications -- Extracting Meningitis Knowledge by Integration of Rule Induction and Association Mining -- Basket Analysis on Meningitis Data -- Extended Genetic Programming Using Apriori Algorithm for Rule Discovery -- Medical Knowledge Discovery on the Meningoencephalitis Diagnosis Studied by the Cascade Model -- Meningitis Data Mining by Cooperatively Using GDT-RS and RSBR. |
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