20 citations · 52 across the 12 of their papers we have counts for
4 papers · 1 filter
The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms
Anirudh Vemula, Yuda Song, Aarti Singh +2
We propose a novel approach to addressing two fundamental challenges in Model-based Reinforcement Learning (MBRL): the computational expense of repeatedly finding a good policy in…
Exploration in Action Space
Anirudh Vemula, Wen Sun, J. Andrew Bagnell
Parameter space exploration methods with black-box optimization have recently been shown to outperform state-of-the-art approaches in continuous control reinforcement learning doma…
Provably Efficient Imitation Learning from Observation Alone
Wen Sun, Anirudh Vemula, Byron Boots +1
We study Imitation Learning (IL) from Observations alone (ILFO) in large-scale MDPs. While most IL algorithms rely on an expert to directly provide actions to the learner, in this…
Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective
Anirudh Vemula, Wen Sun, J. Andrew Bagnell
Black-box optimizers that explore in parameter space have often been shown to outperform more sophisticated action space exploration methods developed specifically for the reinforc…