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

fYear

2010

fDate

27-28 Sept. 2010

Firstpage

287

Lastpage

292

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/SASOW.2010.59

Filename

5729637