Knowledge-Based Multi-agent System for Smart Factory of Small-Sized Manufacturing Enterprises in Korea

2019 ◽  
pp. 81-93
Author(s):  
Byungjun Park ◽  
Jongpil Jeong
Keyword(s):  
Smart Factory ◽  
Multi Agent System ◽  
Agent System ◽  
Manufacturing Enterprises ◽  
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

A Framework to Improve the Disaster Response Through a Knowledge-Based Multi-Agent System

2017 ◽  
Vol 9 (3) ◽  
pp. 96-109
Author(s):  
Claire Prudhomme ◽  
Christophe Cruz ◽  
Ana Roxin ◽  
Frank Boochs
Keyword(s):  
Decision Making ◽  
Information Exchange ◽  
Disaster Response ◽  
Explicit Representation ◽  
Multi Agent System ◽  
Agent System ◽  
Knowledge Based ◽  
Testing Strategies ◽  
Generic Agent ◽  
Multi Agent

The disaster response still faces problems of collaboration due to lack of policies concerning the information exchange during the response. Moreover, plans are prepared to respond to a disaster, but drills to apply them are limited and do not allow to determine their efficiency and conflicts with other organizations. This paper presents a framework allowing for different organizations involving in the disaster response to assess their collaboration through its simulation using an explicit representation of their knowledge. This framework is based on a multi-agent system composed of three generic agent models to represent the organizational structure of disaster response. The decision-making about response actions is done through task decomposition and repartition. It is based reasoning on ontologies which provides an explicit trace of the response plans design and their execution. Such framework aims at identifying cooperation problems and testing strategies of information exchange to support the preparation of disaster response.

Multi-agent system “Smart Factory” for real-time workshop management in aircraft jet engines production

2013 ◽  
Vol 46 (7) ◽  
pp. 204-209 ◽  
Author(s):  
V. Shpilevoy ◽  
A. Shishov ◽  
P. Skobelev ◽  
E. Kolbova ◽  
D. Kazanskaia ◽  
...  
Keyword(s):  
Real Time ◽  
Smart Factory ◽  
Multi Agent System ◽  
Jet Engines ◽  
Agent System ◽  
Multi Agent

scholarly journals Multi-agent system for knowledge-based event recognition and composition

2011 ◽  
Vol 28 (5) ◽  
pp. 488-501 ◽  
Author(s):  
Angel Rivas Casado ◽  
Rafael Martinez-Tomás ◽  
Antonio Fernández-Caballero
Keyword(s):  
Event Recognition ◽  
Multi Agent System ◽  
Agent System ◽  
Knowledge Based ◽  
Multi Agent

scholarly journals Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination

2016 ◽  
Vol 101 ◽  
pp. 158-168 ◽  
Author(s):  
Shiyong Wang ◽  
Jiafu Wan ◽  
Daqiang Zhang ◽  
Di Li ◽  
Chunhua Zhang
Keyword(s):  
Big Data ◽  
Industry 4.0 ◽  
Smart Factory ◽  
Multi Agent System ◽  
Agent System ◽  
Self Organized ◽  
Multi Agent
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