15 citations · 25 across the 5 of their papers we have counts for
3 papers · 1 filter
Reward Reports for Reinforcement Learning
Thomas Krendl Gilbert, Nathan Lambert, Sarah Dean +2
Building systems that are good for society in the face of complex societal effects requires a dynamic approach. Recent approaches to machine learning (ML) documentation have demons…
LiMIIRL: Lightweight Multiple-Intent Inverse Reinforcement Learning
Aaron J. Snoswell, Surya P. N. Singh, Nan Ye
Multiple-Intent Inverse Reinforcement Learning (MI-IRL) seeks to find a reward function ensemble to rationalize demonstrations of different but unlabelled intents. Within the popul…
Revisiting Maximum Entropy Inverse Reinforcement Learning: New Perspectives and Algorithms
Aaron J. Snoswell, Surya P. N. Singh, Nan Ye
We provide new perspectives and inference algorithms for Maximum Entropy (MaxEnt) Inverse Reinforcement Learning (IRL), which provides a principled method to find a most non-commit…