Title : 
Putting the simple recurrent network to the test
         
        
            Author : 
Jodouin, Jean-François
         
        
        
        
        
            Abstract : 
Elman´s simple recurrent network is subjected to systematic empirical analysis. The principal results are that the network, when applied to the prediction task, is: surprisingly robust to variations of its operational parameters over large ranges of values; dependent on the presence of structure in the temporal sequences, to the point where the context memory hinders the network´s learning in totally unstructured domains; and specialized strategies excepted, i.e., incapable of retaining information across embedded inputs exceeding lengths of 2 or 3 tokens
         
        
            Keywords : 
learning (artificial intelligence); performance evaluation; recurrent neural nets; Elman´s simple recurrent network; context memory; learning; temporal sequences; Collaborative work; Feeds; Multilayer perceptrons; Performance evaluation; Robots; Robustness; Testing;
         
        
        
        
            Conference_Titel : 
Neural Networks, 1993., IEEE International Conference on
         
        
            Conference_Location : 
San Francisco, CA
         
        
            Print_ISBN : 
0-7803-0999-5
         
        
        
            DOI : 
10.1109/ICNN.1993.298718