84 citations · 200 across the 12 of their papers we have counts for
23 papers
Causal Imitation Learning under Temporally Correlated Noise
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell +1
We develop algorithms for imitation learning from policy data that was corrupted by temporally correlated noise in expert actions. When noise affects multiple timesteps of recorded…
A Critique of Strictly Batch Imitation Learning
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell +1
Recent work by Jarrett et al. attempts to frame the problem of offline imitation learning (IL) as one of learning a joint energy-based model, with the hope of out-performing standa…
Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell +1
We provide a unifying view of a large family of previous imitation learning algorithms through the lens of moment matching. At its core, our classification scheme is based on wheth…
Feedback in Imitation Learning: The Three Regimes of Covariate Shift
Jonathan Spencer, Sanjiban Choudhury, Arun Venkatraman +2
Imitation learning practitioners have often noted that conditioning policies on previous actions leads to a dramatic divergence between "held out" error and performance of the lear…
CMAX++ : Leveraging Experience in Planning and Execution using Inaccurate Models
Anirudh Vemula, J. Andrew Bagnell, Maxim Likhachev
Given access to accurate dynamical models, modern planning approaches are effective in computing feasible and optimal plans for repetitive robotic tasks. However, it is difficult t…
TRON: A Fast Solver for Trajectory Optimization with Non-Smooth Cost Functions
Anirudh Vemula, J. Andrew Bagnell
Trajectory optimization is an important tool for control and planning of complex, underactuated robots, and has shown impressive results in real world robotic tasks. However, in ap…