Search Results for author: John Hallman

Found 2 papers, 1 papers with code

Deluca -- A Differentiable Control Library: Environments, Methods, and Benchmarking

1 code implementation19 Feb 2021 Paula Gradu, John Hallman, Daniel Suo, Alex Yu, Naman Agarwal, Udaya Ghai, Karan Singh, Cyril Zhang, Anirudha Majumdar, Elad Hazan

We present an open-source library of natively differentiable physics and robotics environments, accompanied by gradient-based control methods and a benchmark-ing suite.

Benchmarking OpenAI Gym

Non-Stochastic Control with Bandit Feedback

no code implementations NeurIPS 2020 Paula Gradu, John Hallman, Elad Hazan

We study the problem of controlling a linear dynamical system with adversarial perturbations where the only feedback available to the controller is the scalar loss, and the loss function itself is unknown.

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