2019
Learning Finite State Representations of Recurrent Policy Networks
ICLR 2019poster
Recurrent neural networks (RNNs) are an effective representation of control policies for a wide range of reinforcement and imitation learning problems. RNN policies, however, are particularly difficult to explain, understand, and analyze due to their use of continuous-valued memory vectors and obser…