An architecture for scalable simulation of systems of cognitive agents
by Tobias Ahlbrecht; Jürgen Dix; Niklas Fiekas; Michael Köster; Philipp Kraus; Jörg P. Müller
International Journal of Agent-Oriented Software Engineering (IJAOSE), Vol. 5, No. 2/3, 2016

Abstract: Using purely agent-based platforms for any kind of simulation requires to address the following challenges: 1) scalability; 2) efficient memory management; 3) modelling. While dedicated professional simulation tools usually provide rich domain libraries and advanced visualisation techniques, and support the simulation of large scenarios, they do not allow for 'agentisation' of single components. We are trying to bridge this gap by developing a distributed, scalable multi-agent simulation platform, MASeRaTi, addressing the three problems mentioned above. It allows to plug-in both dedicated simulation tools as well as the agentisation of certain components of the system. We describe the system architecture, which consists of a lightweight kernel and an agent-modelling layer, on top of which applications reside. An evaluation of the platform is provided by: 1) a proof-of-concept implementation of the well-known cow scenario used in the multi-agent programming contest; 2) experimentally investigating scalability in comparison to the Jason platform.

Online publication date: Sat, 10-Dec-2016

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Agent-Oriented Software Engineering (IJAOSE):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com