10 citations · 10 across the 2 of their papers we have counts for
3 papers
Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation
Mohamad H. Danesh, Maxime Wabartha, Stanley Wu +2
Deploying reinforcement learning (RL) policies in real-world involves significant challenges, including distribution shifts, safety concerns, and the impracticality of direct inter…
On overfitting and asymptotic bias in batch reinforcement learning with partial observability
Vincent Francois-Lavet, Guillaume Rabusseau, Joelle Pineau +2
This paper provides an analysis of the tradeoff between asymptotic bias (suboptimality with unlimited data) and overfitting (additional suboptimality due to limited data) in the co…
Bellman Error Based Feature Generation using Random Projections on Sparse Spaces
Mahdi Milani Fard, Yuri Grinberg, Amir-massoud Farahmand +2
We address the problem of automatic generation of features for value function approximation. Bellman Error Basis Functions (BEBFs) have been shown to improve the error of policy ev…