Title :
Influencing Massive Multi-agent Systems via Viral Trait Spreading
Author :
McLaughlan, Brian ; Hexmoor, Henry
Author_Institution :
Dept. of Comput. Sci., Southern Illinois Univ., Carbondale, IL, USA
Abstract :
This paper describes a method by which a massive multi-agent system can be influenced without resorting to micromanagement. This method could be utilized in the development of meta-reasoning components of individual agents. Agents in the system adopt the traits of their successful peers. The administrator guides this spread of traits through selectively injecting influential agents with modified traits. These key agents are identified via social network analysis techniques. Experimentation is described in which the system is tested for its ability to automatically adopt an acceptable configuration as well as testing the ease in which the administrator is able to guide the system to a better configuration.
Keywords :
computer network reliability; computer viruses; inference mechanisms; multi-agent systems; social networking (online); administrator; individual agents; influential agents; massive multi-agent systems; meta-reasoning components; social network analysis techniques; viral trait spreading; Asia; Context; Humans; Indexes; Mathematical model; Multiagent systems; Social network services;
Conference_Titel :
Self-Adaptive and Self-Organizing Systems Workshop (SASOW), 2010 Fourth IEEE International Conference on
Conference_Location :
Budapest
Print_ISBN :
978-1-4244-8684-7
DOI :
10.1109/SASOW.2010.59
