95 citations · 201 across the 14 of their papers we have counts for
Showing 2020Show all
2 papers · 1 filter
cs.LG2020★ 4 cited
Understanding Learned Reward Functions
Eric J. Michaud, Adam Gleave, Stuart Russell
In many real-world tasks, it is not possible to procedurally specify an RL agent's reward function. In such cases, a reward function must instead be learned from interacting with a…
cs.LG2020
Examining the causal structures of deep neural networks using information theory
Simon Mattsson, Eric J. Michaud, Erik Hoel
Deep Neural Networks (DNNs) are often examined at the level of their response to input, such as analyzing the mutual information between nodes and data sets. Yet DNNs can also be e…