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.

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.

Cannot find the paper you are looking for? You can Submit a new open access paper.