66 citations · 80 across the 10 of their papers we have counts for
3 papers · 1 filter
Automated curriculum generation for Policy Gradients from Demonstrations
Anirudh Srinivasan, Dzmitry Bahdanau, Maxime Chevalier-Boisvert +1
In this paper, we present a technique that improves the process of training an agent (using RL) for instruction following. We develop a training curriculum that uses a nominal numb…
Robo-PlaNet: Learning to Poke in a Day
Maxime Chevalier-Boisvert, Guillaume Alain, Florian Golemo +1
Recently, the Deep Planning Network (PlaNet) approach was introduced as a model-based reinforcement learning method that learns environment dynamics directly from pixel observation…
Option-Critic in Cooperative Multi-agent Systems
Jhelum Chakravorty, Nadeem Ward, Julien Roy +4
In this paper, we investigate learning temporal abstractions in cooperative multi-agent systems, using the options framework (Sutton et al, 1999). First, we address the planning pr…