148 citations · 164 across the 6 of their papers we have counts for
3 papers · 1 filter
SHAPO: Sharpness-Aware Policy Optimization for Safe Exploration
Kaustubh Mani, Yann Pequignot, Vincent Mai +1
Safe exploration is a prerequisite for deploying reinforcement learning (RL) agents in safety-critical domains. In this paper, we approach safe exploration through the lens of epis…
Safety Representations for Safer Policy Learning
Kaustubh Mani, Vincent Mai, Charlie Gauthier +3
Reinforcement learning algorithms typically necessitate extensive exploration of the state space to find optimal policies. However, in safety-critical applications, the risks assoc…
Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation
Vincent Mai, Kaustubh Mani, Liam Paull
In model-free deep reinforcement learning (RL) algorithms, using noisy value estimates to supervise policy evaluation and optimization is detrimental to the sample efficiency. As t…