280 citations · 1.2k across the 24 of their papers we have counts for
4 papers · 1 filter
Balancing Constraints and Rewards with Meta-Gradient D4PG
Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy +4
Deploying Reinforcement Learning (RL) agents to solve real-world applications often requires satisfying complex system constraints. Often the constraint thresholds are incorrectly…
Robust Constrained Reinforcement Learning for Continuous Control with Model Misspecification
Daniel J. Mankowitz, Dan A. Calian, Rae Jeong +5
Many real-world physical control systems are required to satisfy constraints upon deployment. Furthermore, real-world systems are often subject to effects such as non-stationarity,…
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples
Sven Gowal, Chongli Qin, Jonathan Uesato +2
Adversarial training and its variants have become de facto standards for learning robust deep neural networks. In this paper, we explore the landscape around adversarial training i…
Non-Stationary Delayed Bandits with Intermediate Observations
Claire Vernade, Andras Gyorgy, Timothy Mann
Online recommender systems often face long delays in receiving feedback, especially when optimizing for some long-term metrics. While mitigating the effects of delays in learning i…