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Verification of RNN-Based Neural Agent-Environment Systems

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