455 citations · 527 across the 15 of their papers we have counts for
22 papers · 1 filter
Off-Policy Risk Assessment in Markov Decision Processes
Audrey Huang, Liu Leqi, Zachary Chase Lipton +1
Addressing such diverse ends as safety alignment with human preferences, and the efficiency of learning, a growing line of reinforcement learning research focuses on risk functiona…
Finite-time System Identification and Adaptive Control in Autoregressive Exogenous Systems
Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi +1
Autoregressive exogenous (ARX) systems are the general class of input-output dynamical systems used for modeling stochastic linear dynamical systems (LDS) including partially obser…
Meta-Adaptive Nonlinear Control: Theory and Algorithms
Guanya Shi, Kamyar Azizzadenesheli, Michael O'Connell +2
We present an online multi-task learning approach for adaptive nonlinear control, which we call Online Meta-Adaptive Control (OMAC). The goal is to control a nonlinear system subje…
Off-Policy Risk Assessment in Contextual Bandits
Audrey Huang, Liu Leqi, Zachary C. Lipton +1
Even when unable to run experiments, practitioners can evaluate prospective policies, using previously logged data. However, while the bandits literature has adopted a diverse set…
On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk
Audrey Huang, Liu Leqi, Zachary C. Lipton +1
In order to model risk aversion in reinforcement learning, an emerging line of research adapts familiar algorithms to optimize coherent risk functionals, a class that includes cond…
Multi-Agent Multi-Armed Bandits with Limited Communication
Mridul Agarwal, Vaneet Aggarwal, Kamyar Azizzadenesheli
We consider the problem where agents collaboratively interact with an instance of a stochastic arm bandit problem for . The agents aim to simultaneously minimize t…