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Advances in Artificial Intelligence : Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence (JSAI 2019) / / edited by Yukio Ohsawa, Katsutoshi Yada, Takayuki Ito, Yasufumi Takama, Eri Sato-Shimokawara, Akinori Abe, Junichiro Mori, Naohiro Matsumura
| Advances in Artificial Intelligence : Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence (JSAI 2019) / / edited by Yukio Ohsawa, Katsutoshi Yada, Takayuki Ito, Yasufumi Takama, Eri Sato-Shimokawara, Akinori Abe, Junichiro Mori, Naohiro Matsumura |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (307 pages) |
| Disciplina | 006.3 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| ISBN | 3-030-39878-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483498103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Living beyond data : toward sustainable value creation / / edited by Yukio Ohsawa
| Living beyond data : toward sustainable value creation / / edited by Yukio Ohsawa |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (293 pages) |
| Disciplina | 016.403 |
| Collana | Intelligent Systems Reference Library |
| Soggetto topico | Artificial intelligence |
| ISBN |
9783031115936
9783031115929 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Foreword -- Preface: The Reason Why We Seek Living "Beyond Data" -- Contents -- Part I Thoughts and Communication for Living Beyond Data -- 1 Living Beyond Data with Feature Concepts -- 1.1 Introduction: Communications for Discovering Data Utilities -- 1.2 Feature Concepts for Connecting Stakeholders -- 1.3 Examples of Feature Concepts in Data Utilities -- 1.4 Discussion: Feature Concepts as Patters for Living Beyond Data -- 1.5 Conclusions -- References -- 2 Innovation for the Real-World Through Knowing Why -- 2.1 Introduction -- 2.2 Knowing, Uncertainty, and Innovation -- 2.2.1 Ways of Knowing in Innovation -- 2.2.2 Knowing why: Knowing in Situations of Uncertainty and Ambiguity -- 2.2.3 The Observer Problem in Research -- 2.3 Knowing why: Necessity and Capability -- 2.3.1 Necessity: Human Needs and Motivation -- 2.3.2 Capability: Theory-in-Action -- 2.4 Design Practices: Knowing why -- 2.4.1 Necessity: Need-Finding and Benchmarking -- 2.4.2 Capability: Prototyping and Evaluating -- 2.5 Conclusion -- References -- 3 Why Abductive Cognition Goes Beyond Just Learning from Data -- 3.1 Abductive Cognition Generates Knowledge Starting from Data -- 3.1.1 Abduction as Ignorance Preservation -- 3.1.2 Directly Reaching Truth Through Abduction -- 3.2 How Model-Based and Manipulative Abduction Creates Values ``In'' and ``Out'' of Data: The Eco-Cognitive Model (EC-Model) -- 3.2.1 An Example: Construals Create Epistemological Value ``In'' and ``Out'' of Data -- 3.3 Asking ``Why'' Means to Reach Beyond Data: Irrelevance and Implausibility Trigger Creativity -- 3.4 Beyond Learning from Data: Trans-Paradigmatic and Transepistemic Abductions -- 3.5 Can Models Computationally Derived from Data Provide Scientific Knowledge of Physical and Biological Systems?.
3.6 Can Invasive Computational Learning from Big Data Jeopardize Human Creative Abduction in Science? -- 3.7 The Triumph of Shallow Massive Data-Driven Knowledge: Deep Learning and Locked Strategies -- 3.7.1 Reading Ahead -- 3.7.2 Locked Abductive Strategies Acting in a Fixed Scenario of Data Counteract the Maximization of Eco-Cognitive Openness -- 3.7.3 Locking Strategies Restricts Creativity -- 3.8 Conclusion -- References -- 4 Living Labs: A Device That Opens Exploration and Cognitive Generation to Society -- 4.1 Introduction -- 4.2 Overview of European ``Living Labs'' -- 4.2.1 Living Lab's Origins and Founding Intentions -- 4.2.2 Development History of Living Labs -- 4.2.3 Types of Living Labs, Scope of Activities and Methods -- 4.3 The Case of ``Living Labs'' -- 4.3.1 Botnia Living Lab-for Sustainable Smart Cities and Regions -- 4.3.2 HSBC Living Lab, Chalmers University of Technology -- 4.3.3 Trends in Japan -- 4.4 The Essential Features of a Living Labs -- 4.5 A Case Study of Living Labs Based on Its Essential Functions in Iwaki City, Japan -- 4.6 Conclusion -- References -- Part II Explore, Collect, and Use Data -- 5 Interpretability and Explainability in Machine Learning -- 5.1 Introduction -- 5.2 What Is Interpretable Machine Learning? -- 5.3 A Taxonomy of Interpretability Models -- 5.3.1 The Task-Related Latent Dimensions of Interpretability -- 5.3.2 The Method-Related Latent Dimensions of Interpretability -- 5.4 Key Issues of Explainable ML -- 5.5 Conclusion -- References -- 6 Interpretable GAM Models: Predicting Sepsis in ICU Patients -- 6.1 Introduction -- 6.2 Sepsis Prediction -- 6.2.1 Machine Learning in Healthcare -- 6.2.2 GAMs for Sepsis Prediction -- 6.2.3 Problem Definition -- 6.3 Data -- 6.3.1 Origin -- 6.3.2 Identifying Sepsis -- 6.3.3 Data Extraction -- 6.4 Methods -- 6.4.1 General Additive Models -- 6.4.2 Thresholds. 6.5 Results -- 6.5.1 Model Evaluation -- 6.5.2 Model Comparison -- 6.5.3 Focus: upper G upper A squared upper MGA2M Results -- 6.6 Discussion -- 6.6.1 Implications -- 6.6.2 Limitations -- 6.6.3 Future Research -- 6.7 Conclusion -- References -- 7 Undesigned Data in Discovery Processes and Design of Their Interpretation -- 7.1 Introduction -- 7.2 Two Projects as Concrete Examples for Our Discussion -- 7.2.1 Discovering Interesting Travel Routes from Trajectory Data -- 7.2.2 Collecting and Unifying Syllabuses of Various Universities -- 7.3 Models of KDD Process -- 7.3.1 Two Models of KDD Process -- 7.3.2 Hypothesis Validation or Hypothesis Generation -- 7.4 Manipulating Undesigned Data -- 7.4.1 Designed Data and Undesigned Data -- 7.4.2 Undefined Data as Words in Mathematical Logic -- 7.4.3 Designing an Interpretation of Data -- 7.5 Improvement of the KDD Processes -- 7.6 Conclusion and Remarks -- References -- 8 Why Can We Obtain Such an Analysis? -- 8.1 Introduction -- 8.2 (Big) Data Society -- 8.3 Treatment of Data in the World -- 8.4 Abduction and Analogy -- 8.4.1 Philosophical Abduction -- 8.4.2 Computational Abduction -- 8.4.3 The Clause Management System (CMS) -- 8.4.4 Analogical Reasoning -- 8.4.5 Abductive Analogical Reasoning (AAR) -- 8.5 Data Managemant by Abduction and Analogy -- 8.6 Conclusions -- References -- Part III Insights from Cases -- 9 Positive Artificial Intelligence Meets Affective Walkability -- 9.1 Introduction -- 9.2 Positive Artificial Intelligence -- 9.3 Affective Walkability and Urban Design -- 9.4 Positively Intelligent Neighborhoods: A Call to Action -- 9.4.1 In-vitro Experimental Protocol -- 9.4.2 In-vivo Experimental Protocols -- 9.5 Conclusion -- References -- 10 Machine Tells Us New Potential Values-Physics, Perception, and Affective Evaluations -- 10.1 What Is This? Simple and Typical Data for Machine Learning. 10.2 What's This Texture? Affective Data Could be Infinite -- 10.2.1 Texture Expression -- 10.2.2 Experiment Showing the Connection Between Texture and Words -- 10.3 Machine Understands Texture Expressed by Sound-Symbolic Words -- 10.4 Machine Helps to Capture Individual Affective Differences -- 10.5 Machine Generates New Sound-Symbolic Words -- 10.5.1 Method -- 10.5.2 Generating SSWs by Genetic Algorithm -- 10.5.3 Software Implementation -- 10.5.4 Performance Evaluation -- 10.6 Machine Tells Us New Potential Values -- References -- 11 Interactive Sensing and Sensing Interactions -- 11.1 Sensing Living Things and Things to Live With -- 11.1.1 System Outline -- 11.1.2 Area Recognition -- 11.1.3 Activity Recognition -- 11.1.4 Experiment -- 11.1.5 Conclusion -- 11.2 Collecting Human Interest from Interaction ch11SatospsShimokawara2015206 -- 11.2.1 Proposed Category Estimation Method for Chat Robot -- 11.2.2 Experiment -- 11.2.3 Analysis of Category Estimation -- 11.2.4 Summary -- 11.3 Collecting Common Sence from Interaction ch11Aoyagi2018 -- 11.3.1 Research Background -- 11.3.2 An Example of Seasons in a Chat Robot -- 11.3.3 Purpose of This Study -- 11.4 Proposed Method -- 11.4.1 Keywords -- 11.4.2 Template Sentences -- 11.4.3 Recovery Sentences -- 11.5 Experiment -- 11.5.1 The Process of the Experiment -- 11.5.2 Instruction to Subjects -- 11.6 Results and Discussion -- 11.6.1 Users' Responses to the Template Sentences -- 11.6.2 Users' Responses to the Recovery Sentences -- 11.6.3 Additional Experiment -- 11.6.4 Implementation of a System -- 11.6.5 Conclusion -- References -- 12 Simulation-Oriented Data Utilization to Analyze Human Behavior in Urban Traffic Systems -- 12.1 Introduction -- 12.2 Quantifying Value of Traffic System by Forward Analysis -- 12.2.1 Overview of Simulation Model -- 12.2.2 Utilization of Simulation Output Data. 12.3 Estimating Unobservable Demand by Inverse Analysis -- 12.3.1 Estimation Methodology -- 12.3.2 Numerical Experiments -- 12.3.3 Value of Obtaining Data and Reducing Uncertainty -- 12.4 Conclusion -- References -- 13 Externalization of Unexplored Data with Data Origination: Case Analysis of Person-to-Object Contact Data During COVID-19 Pandemic -- 13.1 Introduction -- 13.2 Data Origination -- 13.3 Support Tools for Externalizing Unexplored Data: TEEDA and Variable Quest -- 13.3.1 TEEDA -- 13.3.2 Variable Quest -- 13.4 Unexplored Data Externalization and Analytical Process -- 13.5 Conclusion -- References -- Index. |
| Record Nr. | UNINA-9910629292403321 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
New Frontiers in Artificial Intelligence [[electronic resource] ] : Joint JSAI 2001 Workshop Post-Proceedings / / edited by Takao Terano, Toyoaki Nishida, Akira Namatame, Syrusaku Tsumoto, Yukio Ohsawa, Takashi Washio
| New Frontiers in Artificial Intelligence [[electronic resource] ] : Joint JSAI 2001 Workshop Post-Proceedings / / edited by Takao Terano, Toyoaki Nishida, Akira Namatame, Syrusaku Tsumoto, Yukio Ohsawa, Takashi Washio |
| Edizione | [1st ed. 2001.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 |
| Descrizione fisica | 1 online resource (XXVIII, 556 p.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
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 |
| ISBN | 3-540-45548-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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 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 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. |
| Record Nr. | UNISA-996465331303316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
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
| 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 |
| Edizione | [1st ed. 2001.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 |
| Descrizione fisica | 1 online resource (XXVIII, 556 p.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
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 |
| ISBN | 3-540-45548-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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 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 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. |
| Record Nr. | UNINA-9910143919503321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||