Exploiting the Heavyweight Ontology with Multi-Agent System Using Vocal Command System: A Case Study on E-Mall

2011 ◽  
Vol 3 (6) ◽  
pp. 233-241 ◽  
Author(s):  
Ahmad C. Bukhari ◽  
YongGi Kim
Keyword(s):  
Multi Agent System ◽  
Agent System ◽  
System A ◽  
Multi Agent

Simulating multi-objective land use optimization allocation using Multi-agent system—A case study in Changsha, China

2016 ◽  
Vol 320 ◽  
pp. 334-347 ◽  
Author(s):  
Honghui Zhang ◽  
Yongnian Zeng ◽  
Xiaobin Jin ◽  
Bangrong Shu ◽  
Yinkang Zhou ◽  
...  
Keyword(s):  
Land Use ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Objective ◽  
System A ◽  
Land Use Optimization ◽  
Multi Agent ◽  
Optimization Allocation

Modeling of Multi-Agent System for Drilling Simulation

2011 ◽  
Vol 383-390 ◽  
pp. 1555-1561
Author(s):  
Wu Li Wang ◽  
Yan Jiang Wang
Keyword(s):  
Simulation System ◽  
Drilling Process ◽  
Multi Agent System ◽  
Agent System ◽  
Oil Drilling ◽  
Well Control ◽  
Existing Problems ◽  
System A ◽  
Multi Agent ◽  
Drilling Simulation

In view of the characteristics of the oil drilling process and the existing problems of traditional simulation system, a new distributed drilling simulation model was established based on Multi-Agent system (MAS) technology. By means of autonomous, cooperative and reactive characteristic of Agent, the drilling laws and phenomenon can be reflected promptly and accurately under any circumstances. The MAS modeling for oil drilling simulation, the structure and knowledge representation of each Agent and the communication among Agents are described in detail. Finally, an Agent-based normal drilling well control simulation training example was given. The simulation results show that the simulator based on Multi-Agent system has better performances than traditional drilling simulators, and enhances the integrated training function of the drilling simulation system.

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