40 citations · 148 across the 12 of their papers we have counts for
5 papers · 1 filter
Designing a Prospective COVID-19 Therapeutic with Reinforcement Learning
Marcin J. Skwark, Nicolás López Carranza, Thomas Pierrot +6
The SARS-CoV-2 pandemic has created a global race for a cure. One approach focuses on designing a novel variant of the human angiotensin-converting enzyme 2 (ACE2) that binds more…
Offline Reinforcement Learning Hands-On
Louis Monier, Jakub Kmec, Alexandre Laterre +4
Offline Reinforcement Learning (RL) aims to turn large datasets into powerful decision-making engines without any online interactions with the environment. This great promise has m…
A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning
Arnu Pretorius, Scott Cameron, Elan van Biljon +6
Multi-agent reinforcement learning has recently shown great promise as an approach to networked system control. Arguably, one of the most difficult and important tasks for which la…
Learning Compositional Neural Programs for Continuous Control
Thomas Pierrot, Nicolas Perrin, Feryal Behbahani +4
We propose a novel solution to challenging sparse-reward, continuous control problems that require hierarchical planning at multiple levels of abstraction. Our solution, dubbed Alp…
Diversity Policy Gradient for Sample Efficient Quality-Diversity Optimization
Thomas Pierrot, Valentin Macé, Félix Chalumeau +6
A fascinating aspect of nature lies in its ability to produce a large and diverse collection of organisms that are all high-performing in their niche. By contrast, most AI algorith…