The 5th International Workshop on Emergent Intelligence on Networked Agents (WEIN'13) will be held at AAMAS 2013, the 11th International Joint Conference on Autonomous Agents and Multi-agent Systems, in Saint Paul, Minnesota, USA.
AAMAS will run from May 6–10, 2013, with WEIN'13 being a full-day workshop on May 6. Akira Namatame (National Defense Academy, Japan) will be the WEIN'13 Workshop Chair, assisted by Hideyuki Nakashima (Future University-Hakodate, Japan), Satoshi Kurihara (Osaka University, Japan), and an international Scientific Programme Committee (listed below). See the WEIN'13 workshop web page for more details, including the workshop programme.
In this workshop we will discuss the emergence of intelligence from large-scale complex networked agents. Our brain consists of 50 billion neurons and our consciousness and intelligence emerges from this neural network. At a larger scale, social phenomena emerge from human behaviour and the large-scale complex human network. In these, and other real-world emergence phenomena, not only the dynamics of each neuron or human but also the “network dynamics” are important.
The aim of this workshop is to investigate the role of networked agents in the emergence of systemic properties, notably emergent intelligence. The focus is on topics such as network formation among agents, the feedback of network structures on agent’s dynamics, network-based collective phenomena, and emergent problem solving of networked agents.
Up to now, the main interest of the agent community has been the dynamics of the agent itself. However, in the current rapidly growing Internet tools, such as the WWW and social media like Twitter, Facebook, etc., studies about complex networks are attracting international attention. These studies about complex networks are deeply related to multi agent community. So, the ultimate target of this workshop is to bridge the gap between the multi agent community and the complex systems community.
Currently, it seems that research on MAS is still mostly focused on agents themselves, whereas networks of agents have received relatively little attention. The rapid development of various technologies, including those in web intelligence, ubiquitous computing, sensor networks, and grid computing will, however, lead to systems consisting of a potentially very large number of agents. In these situations, the view of each agent is limited to its local environment, and the efficiency of the system is significantly affected by the network in which the embedded agents. Thus, it is important to pay attention not only to agents themselves, but also to the structure and the dynamics of the network.