Concluding Remarks

FaintPop: In Touch with the Social Relationships

Social Intelligence Design for Communications

In Touch with the Social Relationships

Initial Experiment

Conclusion and Related Works

From Virtual Environment to Virtual Community

Introduction

Towards Multi-user Virtual Worlds

Building a Theater Environment

Interacting about Performances and Environment

Towards a Theater Community

Collaborative Innovation Tools

Importance of Collaboration: Practical and Scientific

New Technological Possibilities

Work of the Knowledge Socialization Group

Bricks & Bits & Interaction

Introduction

Visibility, Awareness, and Interaction in Videoconference Space

Mobile Learners in E-Learning Spaces

Emerging Changes Influenced by Bricks & Bits & Interaction

A Distributed Multi-agent System for the Self-Evaluation of Dialogs

Introduction

System General Architecture

Representation of the Semantic of the Communication Act

Semantic Traits and Agents

Aspectual Agent Organization

The Emerging Meaning of the Communication: The Morphological Agent Organization

Interpretation of the Morphological Organization: The Evocation Agents

Conclusion

Public Opinion Channel: A System for Augmenting Social Intelligence of a Community

Introduction

Communication Costs

POC Prototype System

Evaluation

Discussion

Conclusion

Enabling Public Discourse

Introduction

Enabling Individuals to Collect and Exchange Information and Opinions

Raising Social Awareness through Position-Oriented Discussions

Towards ``Social Intelligence Design''

Concluding Remark

Internet, Discourses, and Democracy

Introduction

Online Support for Democratic Processes

A Novel Participation Methodology

System Design

How to Evaluate Social Intelligence Design

Computer Networked Community as Social Intelligence

The Importance of Control Condition in Evaluating Social Intelligence Design

How to Evaluate POC

Future Works

Part II. Agent-Based Approaches in Economic and Social Complex Systems

Overview

Analyzing Norm Emergence in Communal Sharing via Agent-Based Simulation

Introduction

Related Work on Studies of Norms

Artificial Society Model TRURL

Experiments

Conclusion

Toward Cumulative Progress in Agent-Based Simulation

Introduction

Can We Assist Cumulative Progress?

Exploring Key Elements

Discussion

Conclusions

Complexity of Agents and Complexity of Markets

Introduction

The Efficient Market Hypothesis Seen from Complexity

Artificial Market Model

Simulation Result

New Efficient Market Hypothesis

Conclusion

U-Mart Project: Learning Economic Principles from the Bottom by Both Human and Software Agents

Introduction

Outlines of U-Mart System

Outline of Open Experiment, Pre U-Mart 2000

Participated Agents and Their Strategies

Experimental Result

Experiments with Human Agents

Conclusion and Acknowledgements

A Multi-objective Genetic Algorithm Approach to Construction of Trading Agents for Artificial Market Study

Introduction

The U-Mart System

Multi-objective Genetic Algorithms (MOGA)

Construction of Trading Agents with a MOGA

Results of Experiments

Conclusion

Agent-Based Simulation for Economic and Environmental Studies

Introduction

Agent-Based Simulation Framework: ASIA

Market Simulation

Dynamic Online Auctions

Greenhouse Gas Emissions Trading

Concluding Remarks

Avatamsaka Game Experiment as a Nonlinear Polya Urn Process

Characteristics of Avatamsaka Game

Avatamsaka Game Experiment as a Nonlinear Polya Urn Process

Effects of Punishment into Actions in Social Agents

Introduction

The Tragedy of the Common

Coevolving Levy Plan and Payoff Prediction

Simulation

Conclusion

Analysis of Norms Game with Mutual Choice

Introduction

Mutual Choice in Group Formation

Simulation Setup

Simulation

Conclusion

Cooperative Co-evolution of Multi-agents

Introduction

Evolutionary Approach of IPD Game

Cooperative Co-evolution of Strategies

Experimental Results

Concluding Remarks

Social Interaction as Knowledge Trading Games

Introduction

Knowledge Transaction as Knowledge Trading Games

Knowledge Trading as Symmetric and Asymmetric Coordination Games

Aggregation of Heterogeneous Payoff Matrices

The Collective Behavior in Knowledge Transaction

Conclusion

World Trade League as a Standard Problem for Multi-agent Economics - Concept and Background

Introduction

Concept of World Trade League

Elements of World Trade League

Implementation

Requirements for Standard Problem in Multi-agent Economics

Related Work

Conclusion

Virtual Economy Simulation and Gaming -An Agent Based Approach-

Introduction

Agent Based Simulation Model for Virtual Economy

Result of Simulation

Conclusion

Boxed Economy Foundation Model: Model Framework for Agent-Based Economic Simulations

Introduction

Model Framework for Agent-Based Economic Simulations

Boxed Economy Foundation Model

Applying Boxed Economy Foundation Model

Conclusion

Part III. Rough Set Theory and Granular Computing

Workshop on Rough Set Theory and Granular Computing - Summary

Bayes' Theorem Revised - The Rough Set View

Introduction

Bayes' Theorem

Information Systems and Approximation of Sets

Rough Membership

Information Systems and Decision Rules

Probabilistic Properties of Decision Tables

Decision Tables and Flow Graphs

Comparison of Bayesian and Rough Set Approach

Conclusion

Toward Intelligent Systems: Calculi of Information Granules

Introduction

AR-Schemes

Rough Neural Networks

Decomposition of Information Granules

Soft Computing Pattern Recognition: Principles, Integrations, and Data Mining

Introduction

Relevance of Fuzzy Set Theory in Pattern Recognition

Relevance of Neural Network Approaches

Genetic Algorithms for Pattern Recognition

Integration and Hybrid Systems

Evolutionary Rough Fuzzy MLP

Data Mining and Knowledge Discovery

Identifying Upper and Lower Possibility Distributions with Rough Set Concept

Concepts of Upper and Lower Possibility Distributions

Comparison of Dual Possibility Distributions with Dual Approximations in Rough Sets Theory

Identification of Upper and Lower Possibility Distributions

Conclusions

On Fractals in Information Systems: The First Step

Introduction

Fractal Dimensions

Rough Sets and Topologies on Rough Sets

Fractals in Information Systems

Conclusions

Generalizations of Fuzzy Multisets for Including Infiniteness

Introduction

Multisets and Fuzzy Multisets

Infinite Memberships

A Set-Valued Multiset

Conclusion

Fuzzy c-Means and Mixture Distribution Model for Clustering Based on L1-Space

Introduction

Fuzzy c-Means Based on L1-Space

Mixture Distribution Based on L1-Space

Conclusion

On Rough Sets under Generalized Equivalence Relations

Introduction

The Original Rough Sets

Two Different Problem Settings

Approximation by Means of Elementary Sets

Distinction among Three Regions

Two Procedures for Dependencies among Attributes in a Table with Non-deterministic Information: A Summary

Preliminary

Definitions of NISs

A Way to Obtain All Possible Equivalence Relations

Procedure 1 for Dependencies

Procedure 2 for Dependencies

Execution Time of Every Method

Concluding Remarks

An Application of Extended Simulated Annealing Algorithm to Generate the Learning Data Set for Speech Recognition System

Introduction

Domain Definition for LDS Extraction

The Numerical Formula for LDS Extraction

The Algorithm for Extraction of LDS

Experimental and Result

Conclusion

Generalization of Rough Sets with α-Coverings of the Universe Induced by Conditional Probability Relations

Introduction

Conditional Probability Relations

Generalized Rough Sets Approximation

Conclusions

On Mining Ordering Rules

Introduction

Ordered Information Tables

Mining Ordering Rules

Conclusion

Non-additive Measures by Interval Probability Functions

Introduction

Interval Probability Functions

Combination and Conditional Rules for IPF

Concluding Remarks

Susceptibility to Consensus of Conflict Profiles

Introduction

Conflict Profiles

Susceptibility to Consensus

Conclusions

Analysis of Image Sequences for the Unmanned Aerial Vehicle

Introduction

Data Description

The Task

The Method

Results

Conclusions

The Variable Precision Rough Set Inductive Logic Programming Model and Web Usage Graphs

Introduction

The VPRSILP Model and Web Usage Graphs

Experimental Illustration

Conclusions

Optimistic Priority Weights with an Interval Comparison Matrix

Introduction

Interval AHP with Interval Comparison Matrix

Choice of Optimistic Weights and Efficiency by DEA

Numerical Example

Concluding Remarks

Rough Set Theory in Conflict Analysis

Introduction

Conflict Model

Analysis

Conclusions

Dealing with Imperfect Data by RS-ILP

Introduction

Imperfect Data in ILP

RS-ILP for Missing Classification

RS-ILP for Too Strong Bias

Concluding Remarks

Extracting Patterns Using Information Granules: A Brief Introduction

Introduction

Granule Decomposition

Classification Models Based on Approximate Bayesian Networks

Introduction

Frequencies in Data

Approximate Independence

Bayesian Classification

Approximate Bayesian Networks

Conclusions

Identifying Adaptable Components - A Rough Sets Style Approach

Introduction

Defining Adaptation of Software Components

Identifying One-to-One Component Adaptation

Identifying One-to-Many Component Adaptation

Conclusions

Rough Measures and Integrals: A Brief Introduction

Introduction

Classical Additive Set Functions

Basic Concepts of Rough Sets

Rough Integrals

Relevance of a Sensor

Conclusion

Association Rules in Semantically Rich Relations: Granular Computing Approach

Introduction

Relational Models and Rough Granular Structures

Databases with Additional Semantics

Mining Real World or Its Representations

Clustered Association Rules-Mining Semantically

Conclusion

A Note on Filtration and Granular Reasoning

Introduction

Preliminaries

Relative Filtration with Approximation

Example of Granular Reasoning

Concluding Remarks

A Note on Conditional Logic and Association Rules

Introduction

Association Rules

Previous Works

Graded Conditional Logic

Concluding Remarks

Analysis of Self-Injurious Behavior by the LERS Data Mining System

Introduction

Data Mining

Results

Conclusions

A Clustering Method for Nominal and Numerical Data Based on Rough Set Theory

Introduction

Clustering Method

Experimental Results

Conclusions

A Design of Architecture for Rough Set Processor

Introduction

Architecture

Conclusion

Part IV. Chance Discovery

The Scope of Chance Discovery

Chance Discovery Using Dialectical Argumentation

Introduction

Argumentation

The Discovery Agora: Formal Structure

Conclusion

Methodological Considerations on Chance Discovery

Introduction

Nature vs. Open Systems

Chance Discovery in Open Systems

Chance Discovery, Uncertainty, Freedom

Scientific Evaluation of Theories

Chance Discovery vs. KDD

Discussion and Conclusion

Future Directions of Communities on the Web

Introduction

Related Researches

Future Directions of Communities

Experiments and Discussions

Conclusions

A Document as a Small World

Introduction

Small World

Term Co-occurrence Graph

Finding Important Terms

Example

Conclusion

Support System for Creative Activity by Information Acquirement through Internet

Introduction

Framework for Creative Activity

Experimental System

Conclusion

An Approach to Support Long-Term Creative Thinking and Its Feasibility

Introduction

System Overview

Long-Term User Study

Conclusions

Chance Discovery by Creative Communicators Observed in Real Shopping Behavior

Introduction

Collecting Protocols of Actual Purchase Activities

Analysis and Result

Discussion

The Role of Counterexamples in Discovery Learning Environment: Awareness of the Chance for Learning

Introduction

Chance Discovery in Learning Environment

How to Design Effective Counterexamples

Designing `Visible' Counterexamples

Discussion

Integrating Data Mining Techniques and Design Information Management for Failure Prevention

Introduction

Fault Detection of Spacecraft by Mining Association Rules of Housekeeping Data

Managing Information for Failure Prevention

Current Work and Conclusions

Action Proposal as Discovery of Context (An Application to Family Risk Management)

Introduction: Which Opinions Grow into Consensus?

KeyGraph for Noticing Consensus Seeds from Questionnaire

Family Perception of Risks and Opportunities

Conclusions

Retrieval of Similar Time-Series Patterns for Chance Discovery

Introduction

Reference Interval-Free Active Search

Experiments

Summary

Fuzzy Knowledge Based Systems and Chance Discovery

Introduction

Fuzzy Knowledge Based Systems

System Architecture

Conclusions

Part V. 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

Introduction

Ontologies for Inductive Learning

Basic Design of CAMLET

A Case Study of Knowledge Discovery Support Using a Meningoencephalitis Dataset

Conclusions and Future Work

Extracting Meningitis Knowledge by Integration of Rule Induction and Association Mining

Introduction

LUPC: Learning Unbalanced Positive Class

Finding Rules from Meningitis Data

Conclusion

Basket Analysis on Meningitis Data

Introduction

Method for Selection and Discretization

Application

Result and Expert's Evaluation

Conclusion

Extended Genetic Programming Using Apriori Algorithm for Rule Discovery

Introduction

Genetic Programming

Approach of Proposed Combined Learning

Apply to Rule Discovery from Database

Conclusions

Medical Knowledge Discovery on the Meningoencephalitis Diagnosis Studied by the Cascade Model

Introduction

The Cascade Model

Concluding Remarks

Meningitis Data Mining by Cooperatively Using GDT-RS and RSBR

Introduction

Rule Discovery by GDT-RS

Discretization Based on RSBR

Application in Meningitis Data Mining

Conclusion

Author Index

Subject Index