EMERALD: A Multi-Agent System for Knowledge-Based Reasoning Interoperability in the Semantic Web

2010 ◽  
pp. 173-182 ◽  
Author(s):  
Kalliopi Kravari ◽  
Efstratios Kontopoulos ◽  
Nick Bassiliades
Keyword(s):  
Semantic Web ◽  
Multi Agent System ◽  
Agent System ◽  
Knowledge Based ◽  
Multi Agent

VERIFICATION OF THE MOBILE AGENT NETWORK SIMULATOR — A TOOL FOR SIMULATING MULTI-AGENT SYSTEMS

2008 ◽  
Vol 18 (05) ◽  
pp. 651-682 ◽  
Author(s):  
MARIO KUSEK ◽  
KRESIMIR JURASOVIC ◽  
GORDAN JEZIC
Keyword(s):  
Mobile Agent ◽  
Formal Model ◽  
Task Complexity ◽  
Network Simulator ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Network Bandwidth ◽  
Knowledge Based ◽  
Multi Agent

This paper deals with the verification of a multi-agent system simulator. Agents in the simulator are based on the Mobile Agent Network (MAN) formal model. It describes a shared plan representing a process which allows team formation according to task complexity and the characteristics of the distributed environment where these tasks should be performed. In order to verify the simulation results, we compared them with performance characteristics of a real multi-agent system, called the Multi-Agent Remote Maintenance Shell (MA–RMS). MA–RMS is organized as a team-oriented knowledge based system responsible for distributed software management. The results are compared and analyzed for various testing scenarios which differ with respect to network bandwidth as well as task and network complexity.

scholarly journals Multi-agent system for Knowledge-based recommendation of Learning Objects

2015 ◽  
Vol 4 (1) ◽  
pp. 80 ◽  
Author(s):  
Paula Andrea RODRÍGUEZ MARÍN ◽  
Néstor DUQUE ◽  
Demetrio OVALLE
Keyword(s):  
Learning Objects ◽  
Multi Agent System ◽  
Agent System ◽  
Knowledge Based ◽  
Multi Agent

Knowledge Technologies-Based Multi-Agent System for Semantic Web Services Environments

2008 ◽  
pp. 1222-1233
Author(s):  
Francisco García-Sánchez ◽  
Rodrigo Martínez-Béjar ◽  
Rafael Valencia-García ◽  
Jesualdo T. Fernández-Breis
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Semantic Web Services ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent

MASTER: AN INTELLIGENT ONTOLOGY-BASED MULTI-AGENT SYSTEM FOR SIGHTSEER

2009 ◽  
Vol 19 (02) ◽  
pp. 137-157 ◽  
Author(s):  
TOBY H. W. LAM ◽  
JAMES N. K. LIU ◽  
RAYMOND S. T. LEE
Keyword(s):  
Semantic Web ◽  
Structural Information ◽  
Domain Ontology ◽  
Multi Agent System ◽  
Markup Languages ◽  
Agent System ◽  
Web Technologies ◽  
Ontology Language ◽  
Multi Agent ◽  
Tourist Information

Recently, semantic web has received substantial attention from the research community. Semantic web aims to provide a new framework that can enable knowledge sharing and reusing. Semantic web is a collection of web technologies that include a number of markup languages such as RDF, OWL and RDFS. These markup languages are used for modeling a domain ontology. By using ontology to model resources, humans and computers (software agents) can have a consensus on the resource structure. The use of these technologies allows the creation of a more effective web search system. In this paper, we modeled travel domain ontology by using Web Ontology Language (OWL). Instead of inviting an expert to model the ontology, we created the travel ontology by collecting and analyzing the structural information from a number of travel related websites. Besides, we implemented an intelligent ontology-based Multi-Agent System for sighTseER (MASTER), which is constructed by using semantic web technologies. MASTER integrates Global Positioning System (GPS), ontology and agent technologies to support location awareness for providing the precise navigation and classify the tourist information for the users. The system was tested on 30 novice users. 83% of the users felt that the system can help tourists find tourist information in Hong Kong.

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