Innovative approaches in agent-based modelling and business intelligence /
[Book]
Setsuya Kurahashi, Hiroshi Takahashi, editors.
Singapore :
Springer,
2018.
1 online resource
Agent-based social systems ;
12
Includes bibliographical references.
Intro; Preface; Contents; 1 Gallery for Evolutionary Computation and Artificial Intelligence Researches: Where Do We Come from and Where Shall We Go; 1.1 The Shape of Jazz to Come: Introduction; 1.2 A Child Is Born: When Experimental Methods Started; 1.3 Now or Never: Why Not Now; 1.4 Pick Up the Pieces: What Are Elements; 1.5 Place to Be: Where Should We Focus On; 1.6 Act Your Age: Which Way to Go; 1.7 Adios Nonino: Concluding Remarks; References; 2 Mathematical Technologies and Artificial Intelligence Toward Human-Centric Innovation; 2.1 Introduction; 2.2 Social Mathematics Approaches
2.3 Case Studies2.3.1 Congestion Reduction in a Place Where People Gather: The Case of Fukuoka Airport (Fujitsu Press Releases 2015; Yamada et al. 2017); 2.3.1.1 Background; 2.3.1.2 Problem Situation; 2.3.1.3 System Design Process; 2.3.2 Promotion of Relocation from Urban Areas to Countryside: The Case of Itoshima City (Fujitsu Press Releases 2016); 2.3.2.1 Background; 2.3.2.2 Problem Situation; 2.3.2.3 System Design Process; 2.3.3 Support of Daycare Admissions Screening: The Case of Saitama City (Fujitsu Press Releases 2017); 2.3.3.1 Background; 2.3.3.2 Problem Situation
2.3.3.3 System Design Process2.4 Discussion; 2.4.1 Development Technologies; 2.4.2 System Design Processes; 2.4.2.1 Step 2 System Development; 2.4.2.2 Step 3 System Evaluation; 2.5 Conclusion; References; 3 Study on the Social Perspectives of Traffic Congestion in Sri Lanka Through Agent-Based Modeling and Simulation: Lessons Learned and Future Prospects; 3.1 Introduction; 3.2 Complexity, Agent-Based Modeling, and Traffic Simulation; 3.3 The Seepage Behavior and Its Impact on Road Traffic; 3.4 Future Prospects; 3.5 Conclusion; References; 4 Information Technology and Finance; 4.1 Introduction
4.2 Influence of Information Technology4.2.1 On Occupation; 4.2.2 On Corporations; 4.2.3 On Organizations; 4.2.4 On Financial Research; 4.3 Application to Financial Analysis: Agent-Based Model; 4.3.1 Model; 4.3.2 Outline of Experimental Results: Effectiveness of Fundamental Index; 4.4 Conclusion; References; 5 Two Phase Transitions in the Adaptive Voter Model Based on the Homophily Principle; 5.1 Introduction; 5.2 Related Work; 5.3 Homophily Principle; 5.4 Generalized Adaptive Voter Model; 5.5 Simulation; 5.5.1 Objective; 5.5.2 Method; 5.5.3 Network Evolution; 5.5.4 Global Consensus
5.5.5 Fragmentation Transition5.5.6 Phase Diagram; 5.5.7 Modularity Change; 5.6 Conclusion; References; 6 Sensitivity Analysis in a Bayesian Network for Modeling an Agent; 6.1 Introduction; 6.2 Related Work; 6.2.1 Bayesian Network; 6.2.2 Feature Selection; 6.3 Proposed Method; 6.4 Case Study of Healthcare Home Electronics: Blood-Pressure Monitor and Activity Monitor; 6.4.1 Consumer Survey Data Used; 6.4.2 Fundamental Statistical Results; 6.4.3 Learned Bayesian Network Structure; 6.4.3.1 Features or Attributes; 6.4.3.2 Feature Selection; 6.4.3.3 Graph Structures of Bayesian Network
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This book thoroughly prepares intermediate-level readers for research in social science, organization studies, economics, finance, marketing science, and business science as complex adaptive systems. It presents the advantages of social simulation studies and business intelligence to those who are not familiar with the computational research approach, and offers experienced modelers various instructive examples of using agent-based modeling and business intelligence approaches to inspire their own work. In addition, the book discusses cutting-edge techniques for complex adaptive systems using their applications. To date, business science studies have focused only on data science and analyses of business problems. However, using these studies to enhance the capabilities of conventional techniques in the fields has not been investigated adequately. This book addresses managing the issues of societies, firms, and organizations to profit from interaction with agent-based modeling, human- and computer- mixed systems, and business intelligence approaches, an area that is fundamental for complex but bounded rational business environments. With detailed research by leading authors in the field, Innovative Approaches in Agent-Based Modelling and Business Intelligence inspires readers to join with other disciplines and extend the scope of the book with their own unique contributions. It also includes the common challenges encountered in computational social science and business science to enable researchers, students, and professionals to resolve their own problems.
Springer Nature
com.springer.onix.9789811318498
Innovative approaches in agent-based modelling and business intelligence.