Research of Multi-Agent System Model and Learning Method

2005 ◽  
Author(s):  
Yong-mei Zhang ◽  
Yan Han
Keyword(s):  
System Model ◽  
Learning Method ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent

Determination of Factors Affecting Safety Stress in Machine Design by Using Artificial Intelligence Technologies

2008 ◽  
Vol 144 ◽  
pp. 232-237
Author(s):  
Durmus Karayel ◽  
Sinan Serdar Ozkan ◽  
Fahri Vatansever
Keyword(s):  
Artificial Intelligence ◽  
Information Technologies ◽  
Intelligent System ◽  
System Model ◽  
Multi Agent System ◽  
Safety Factors ◽  
Agent System ◽  
Factors Affecting ◽  
Classical Design ◽  
Multi Agent

In this study, an intelligent system model that can evaluate experimental material properties and safety factors is developed. The model contains Artificial Intelligence Technologies such as Artificial Neural Network (ANN) and Fuzzy Logic. It consists of sub modules into interaction. Also, the model can obtain more precision values than interpolation techniques used to classical design. The study contributes to define safety factors, design criterions and safety stress according to a new approach based on information technologies. So, this study can be seen as one of the sub modules of Intelligence Multi Agent System and it can be integrated with Multi Agent System Model for design. Also, it can be used for classical design studies so that results can be quickly obtained. It is expected that this approach will be widely used by designers.

MAS Learning Based on Bayesian Learning Method

2010 ◽  
Vol 20-23 ◽  
pp. 1292-1298
Author(s):  
De Jia Shi ◽  
Zhi Qiang Liu ◽  
Jing He
Keyword(s):  
Learning Strategies ◽  
Bayesian Learning ◽  
Free Text ◽  
Learning Approach ◽  
Learning Method ◽  
Multi Agent System ◽  
Agent System ◽  
Agent Learning ◽  
Multi Agent ◽  
Keyword Searches

Mulit-agent system[MAS] research on learning has been in the area of negotiation, and learning strategies of other agents.This paper presents an agent learning approach in multi-agent system based on Bayesian learning, it researches to develop agents that learn free-text queries and keyword searches in MAS. The MAS learns to identify an appropriate agent to answer free-text and natural language queries as well as keyword searches submitted by users. The paper describes how Bayesian learning is implemented in MAS, and analyzes the effectiveness of MAS learning based on the Bayesian learning approach by analyzing the accuracy and degree of learning.

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