Title : 
Towards the knowledge-based multi-agent system identification
         
        
        
            Author_Institution : 
V.A. Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences, Moscow, Russia
         
        
        
            fDate : 
6/1/2015 12:00:00 AM
         
        
        
        
            Abstract : 
An approach to problem-oriented learning of a multi-agent system is proposed. The corresponding methods apply a kind of such a notion as knowledge and the introduced notion of φ-linear models that are a specific class of general nonlinear ones. Specifically, the values of transfer coefficients were shown to be adapted to the solved identification problem and are in sequel used by the multi-agent system to form the problem-oriented knowledge about the object under study, and updating the knowledge base.
         
        
            Keywords : 
"Yttrium","Entropy","Multi-agent systems","Standards","Gaussian distribution","Mathematical model","Knowledge based systems"
         
        
        
            Conference_Titel : 
Industrial Electronics and Applications (ICIEA), 2015 IEEE 10th Conference on
         
        
        
            DOI : 
10.1109/ICIEA.2015.7334146