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.

Incremental Development of Networked Intelligence in Flocking Behavior.- Emergence and Software development Based on a Survey of Emergence Definitions.- The Impact of Network Model on Performance of Load-balancing.- Auction-Based Resource Reservation Game in Small World.- Navigational Information as Emergent Intelligence of Spontaneously Structuring Web Space.- From Agents to Communities: A Meta-model for Community Computing in Multi-Agent System.- The effects of market structure on a heterogeneous evolving population of traders.- Analysis on Transport Networks of Railway, Subway and Waterbus in Japan.- Network Design via Flow Optimization.- Gibbs measures for the network.- Extracting Users' Interests of Web-watching Behaviors Based on Site-Keyword Graph.- Topological aspects of protein networks.- Collective Intelligence of Networked Agents.- Using an agent based simulation to evaluate scenarios in customers' buying behaviour.- How to Form Stable and Robust Network Structure through Agent Learning—from the viewpoint of a resource sharing problem.- An Evolutionary Rulebase Based Multi-agents System.- Improvements in Performance of Large-Scale Multi-Agent Systems Based on the Adaptive/ Non-Adaptive Agent Selection.- Effect of grouping on classroom communities.- Emergence and Evolution of Coalitions in Buyer-Seller Networks.

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 intelligence on 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.