Smart Modeling and Simulation for Complex Systems

1. Front Matter

   Pages i-viii

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2. HIPRank: Ranking Nodes by Influence Propagation Based on Authority and Hub

   • Wen Zhang, Song Wang, Guangle Han, Ye Yang, Qing Wang

   Pages 1-14

3. Benefits of Generalised Microsimulation

   • Daniel Keep, Ian Piper, Anthony Green

   Pages 15-27

4. From Global Polarization to Local Social Mechanisms: A Study Based on ABM and Empirical Data Analysis

   • Zhenpeng Li, Xijin Tang

   Pages 29-40

5. Decentralised Task Allocation Under Space, Time and Communication Constraints in Disaster Domains

   • Xing Su, Minjie Zhang, Quan Bai

   Pages 41-57

6. Describing and Evaluating Assistance Using APDL

   • Martin Nyolt, Alexander Steiniger, Sebastian Bader, Thomas Kirste

   Pages 59-81

7. A Relaxation Strategy with Fuzzy Constraints for Supplier Selection in a Power Market

   • Dien Tuan Le, Minjie Zhang, Fenghui Ren

   Pages 83-97

8. Idea Discovery: A Context-Awareness Dynamic System Approach for Computational Creativity

   • Hao Wang, Yukio Ohsawa, Xiaohui Hu, Fanjiang Xu

   Pages 99-111

9. Hierarchical Scoring Rule Based Smart Dynamic Electricity Pricing Scheme

   • Shantanu Chakraborty, Takayuki Ito

   Pages 113-131

10. Evaluation of Route Assignment Method with Anticipatory Stigmergy Under Distributed Processing Environment

    • Jun Takahashi, Ryo Kanamori, Takayuki Ito

    Pages 133-145

11. Back Matter

    Pages 147-149

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This book aims to provide a description of these new Artificial Intelligence technologies and approaches to the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field such as the platforms and/or the software tools for smart modeling and simulating complex systems. These tasks are difficult to accomplish using traditional computational approaches due to the complex relationships of components and distributed features of resources, as well as the dynamic work environments. In order to effectively model the complex systems, intelligent technologies such as multi-agent systems and smart grids are employed to model and simulate the complex systems in the areas of ecosystem, social and economic organization, web-based grid service, transportation systems, power systems and evacuation systems.

• Complex System
• Multi-agent System
• SSMCS
• Smart City
• Smart Grid
• Smart Modeling and Simulation
• complexity

• Auckland University of Technology, Auckland, New Zealand

  Quan Bai

• University of Wollongong, Wollongong, Australia

  Fenghui Ren

• School of Computer Science and Software, University of Wollongong, Wollongong, Australia

  Minjie Zhang

• Nagoya Institute of Technology, Nagoya, Japan

  Takayuki Ito

• Academy of Mathematics and Systems Science, Chinese Academy of Science, Beijing, China

  Xijin Tang

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