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Emergent Intelligence of Networked Agents

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  • © 2007

Overview

Editors:
  1. Akira Namatame

    1. Department of Computer Science, National Defense Academy, Yokosuka, Japan

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  2. Satoshi Kurihara

    1. Graduate School of Information Science and Technology, Osaka University, Osaka, Japan

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  3. Hideyuki Nakashima

    1. Future University-Hakodate, Hokkaido, Japan

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  • Contains the latest research on Emergent Intelligence of Networked Agents
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Computational Intelligence (SCI, volume 56)

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Table of contents (19 chapters)

  1. Front Matter

    Pages i-xi
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  2. Incremental Development of Networked Intelligence in Flocking Behavior

    • Masaru Aoyagi, Akira Namatame
    Pages 1-12

  3. Emergence and Software development Based on a Survey of Emergence Definitions

    • Joris Deguet, Laurent Magnin, Yves Demazeau
    Pages 13-21

  4. The Impact of Network Model on Performance of Load-balancing

    • Kensuke Fukuda, Toshio Hirotsu, Satoshi Kurihara, Osamu Akashi, Shin-ya Sato, Toshiharu Sugawara
    Pages 23-37

  5. Auction-Based Resource Reservation Game in Small World

    • Zhixing Huang, Yan Tang, Yuhui Qiu
    Pages 39-51

  6. Navigational Information as Emergent Intelligence of Spontaneously Structuring Web Space

    • Takashi Ishikawa
    Pages 53-65

  7. From Agents to Communities: A Meta-model for Community Computing in Multi-Agent System

    • Kyengwhan Jee, Jung-Jin Yang
    Pages 67-81

  8. The effects of market structure on a heterogeneous evolving population of traders

    • Dan Ladley, Seth Bullock
    Pages 83-97

  9. Analysis on Transport Networks of Railway, Subway and Waterbus in Japan

    • Takahiro Majima, Mitujiro Katuhara, Keiki Takadama
    Pages 99-113

  10. Network Design via Flow Optimization

    • Yusuke Matsumura, Hidenori Kawamura, Koichi Kurumatani, Azuma Ohuchi
    Pages 115-128

  11. Gibbs measures for the network

    • Syuji Miyazaki
    Pages 129-137

  12. Extracting Users' Interests of Web-watching Behaviors Based on Site-Keyword Graph

    • Tsuyoshi Murata, Kota Saito
    Pages 139-146

  13. Topological aspects of protein networks

    • J. C. Nacher, M. Hayashida, T. Akutsu
    Pages 147-158

  14. Collective Intelligence of Networked Agents

    • Akira Namatame
    Pages 159-176

  15. Using an agent based simulation to evaluate scenarios in customers' buying behaviour

    • Filippo Neri
    Pages 177-188

  16. How to Form Stable and Robust Network Structure through Agent Learning—from the viewpoint of a resource sharing problem

    • Itsuki Noda, Masayuki Ohta
    Pages 189-201

  17. An Evolutionary Rulebase Based Multi-agents System

    • Hiroshi Ouchiyama, Runhe Huang, Jianhua Ma
    Pages 203-215

  18. Improvements in Performance of Large-Scale Multi-Agent Systems Based on the Adaptive/ Non-Adaptive Agent Selection

    • Toshiharu Sugawara, Kensuke Fukuda, Toshio Hirotsu, Shin-ya Sato, Satoshi Kurihara
    Pages 217-230

  19. Effect of grouping on classroom communities

    • Toriumi Fujio, Ishii Kenichiro
    Pages 231-243

  20. Emergence and Evolution of Coalitions in Buyer-Seller Networks

    • Frank E. Walter, Stefano Battiston, Frank Schweitzer
    Pages 245-258
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Keywords

About this book

The study of intelligence emerged from interactions among agents has been popular. In this study it is recognized that a network structure of the agents plays an important role. The current state-of-the art in agent-based modeling tends to be a mass of agents that have a series of states that they can express as a result of the network structure in which they are embedded. Agent interactions of all kinds are usually structured with complex networks. The idea of combining multi-agent systems and complex networks is also particularly rich and fresh to foster the research on the study of very large-scale multi-agent systems. Yet our tools to model, understand, and predict dynamic agent interactions and their behavior on complex networks have lagged far behind. Even recent progress in network modeling has not yet offered us any capability to model dynamic processes among agents who interact at all scales on complex networks. This book is based on communications given at the Workshop on Emergent Intelligence of Networked Agents (WEIN 06) at the Fifth International Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2006), which was held at Future University, Hakodate, Japan, from May 8 to 12, 2006. WEIN 06 was especially intended to increase the awareness of researchers in these two fields sharing the common view on combining agent-based modeling and complex networks in order to develop insight and foster predictive methodologies in studying emergent intelligenceon of networked agents. From the broad spectrum of activities, leading experts presented important paper and numerous practical problems appear throughout this book. The papers contained in this book are concerned with emergence of intelligent behaviors over networked agents and fostering the formation of an active multi-disciplinary community on multi-agent systems and complex networks.

Editors and Affiliations

  • Department of Computer Science, National Defense Academy, Yokosuka, Japan

    Akira Namatame

  • Graduate School of Information Science and Technology, Osaka University, Osaka, Japan

    Satoshi Kurihara

  • Future University-Hakodate, Hokkaido, Japan

    Hideyuki Nakashima

Bibliographic Information

  • Book Title: Emergent Intelligence of Networked Agents

  • Editors: Akira Namatame, Satoshi Kurihara, Hideyuki Nakashima

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-540-71075-2

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2007

  • Hardcover ISBN: 978-3-540-71073-8Published: 03 May 2007

  • Softcover ISBN: 978-3-642-09014-1Published: 22 November 2010

  • eBook ISBN: 978-3-540-71075-2Published: 25 April 2007

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XII, 258

  • Number of Illustrations: 105 b/w illustrations

  • Topics: Artificial Intelligence, Mathematical and Computational Engineering

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