Residual Policy Learning

1 code implementation • 15 Dec 2018 • Tom Silver, Kelsey Allen, Josh Tenenbaum, Leslie Kaelbling

In these tasks, reinforcement learning from scratch remains data-inefficient or intractable, but learning a residual on top of the initial controller can yield substantial improvements.

reinforcement-learning

End-to-End Differentiable Physics for Learning and Control

1 code implementation • NeurIPS 2018 • Filipe de Avila Belbute-Peres, Kevin Smith, Kelsey Allen, Josh Tenenbaum, J. Zico Kolter

We present a differentiable physics engine that can be integrated as a module in deep neural networks for end-to-end learning.

Relational inductive biases, deep learning, and graph networks

27 code implementations • 4 Jun 2018 • Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Caglar Gulcehre, Francis Song, Andrew Ballard, Justin Gilmer, George Dahl, Ashish Vaswani, Kelsey Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matt Botvinick, Oriol Vinyals, Yujia Li, Razvan Pascanu

As a companion to this paper, we have released an open-source software library for building graph networks, with demonstrations of how to use them in practice.

Decision Making Relational Reasoning

Detecting Disagreement in Conversations using Pseudo-Monologic Rhetorical Structure

no code implementations • EMNLP 2014 • Kelsey Allen, Giuseppe Carenini, Raymond Ng