Using Bisimulation Metrics to Analyze and Evaluate Latent State Representations

Deep Reinforcement Learning (RL) is a promising technique towards constructing intelligent agents, but it is not always easy to understand the learning process and the factors that impact it. To shed some light on this, we analyze the Latent State Representations (LSRs) that deep RL agents learn, and compare them to what such agents should...

Learning What to Attend to: Using Bisimulation Metrics to Explore and Improve Upon What a Deep Reinforcement Learning Agent Learns

Recent years have seen a surge of algorithms and architectures for deep Re-<br/>inforcement Learning (RL), many of which have shown remarkable success for<br/>various problems. Yet, little work has attempted to relate the performance of<br/>these algorithms and architectures to what the resulting deep RL agents actu-<br/>ally learn, and whether...