Proto-Predictive Representation of States with Simple Recurrent Temporal-Difference Networks

We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable environments. SR-TDNs i