Search Results for author: Josh S. Merel

Found 2 papers, 1 papers with code

RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning

1 code implementation NeurIPS 2020 Caglar Gulcehre, Ziyu Wang, Alexander Novikov, Thomas Paine, Sergio Gómez, Konrad Zolna, Rishabh Agarwal, Josh S. Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matthew Hoffman, Nicolas Heess, Nando de Freitas

We hope that our suite of benchmarks will increase the reproducibility of experiments and make it possible to study challenging tasks with a limited computational budget, thus making RL research both more systematic and more accessible across the community.

Benchmark Offline RL +1

A multi-agent control framework for co-adaptation in brain-computer interfaces

no code implementations NeurIPS 2013 Josh S. Merel, Roy Fox, Tony Jebara, Liam Paninski

In a closed-loop brain-computer interface (BCI), adaptive decoders are used to learn parameters suited to decoding the user's neural response.

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