Verification of RNN-Based Neural Agent-Environment Systems
              Author
              
  
            
                                  
              Abstract
              
  
    
              
          
            
                                  We introduce agent-environment systems where the agent is stateful and executing a ReLU recurrent neural network. We define and study their verification problem by providing equivalences of recurrent and feed-forward neural networks on bounded execution traces. We give a sound and complete procedure for their verification against properties specified in a simplified version of LTL on bounded executions. We present an implementation and discuss the experimental results obtained.
              Year of Conference
              
  
    
              
            
                                  2019
          
              Conference Name
              
  
    
              
            
                                  AAAI Conference on Artificial Intelligence
          
              Edition
              
  
    
              
            
                                  Thirty-Third 
          
              Publisher
              
  
    
              
            
                                  
                                  Association for the Advancement of Artificial Intelligence
          
              DOI
              
  
    
              
            
                                  https://doi.org/10.1609/aaai.v33i01.33016006