177 citations · 387 across the 12 of their papers we have counts for
3 papers · 2 filters
Memory Lens: How Much Memory Does an Agent Use?
Christoph Dann, Katja Hofmann, Sebastian Nowozin
We propose a new method to study the internal memory used by reinforcement learning policies. We estimate the amount of relevant past information by estimating mutual information b…
A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games
Felix Leibfried, Nate Kushman, Katja Hofmann
Reinforcement learning is concerned with identifying reward-maximizing behaviour policies in environments that are initially unknown. State-of-the-art reinforcement learning approa…
Experimental and causal view on information integration in autonomous agents
Philipp Geiger, Katja Hofmann, Bernhard Schölkopf
The amount of digitally available but heterogeneous information about the world is remarkable, and new technologies such as self-driving cars, smart homes, or the internet of thing…