57 citations · 69 across the 2 of their papers we have counts for
3 papers
Enforcing robust control guarantees within neural network policies
Priya L. Donti, Melrose Roderick, Mahyar Fazlyab +1
When designing controllers for safety-critical systems, practitioners often face a challenging tradeoff between robustness and performance. While robust control methods provide rig…
Provably Safe PAC-MDP Exploration Using Analogies
Melrose Roderick, Vaishnavh Nagarajan, J. Zico Kolter
A key challenge in applying reinforcement learning to safety-critical domains is understanding how to balance exploration (needed to attain good performance on the task) with safet…
Implementing the Deep Q-Network
Melrose Roderick, James MacGlashan, Stefanie Tellex
The Deep Q-Network proposed by Mnih et al. [2015] has become a benchmark and building point for much deep reinforcement learning research. However, replicating results for complex…