21 citations · 38 across the 4 of their papers we have counts for
5 papers
Mimicking Better by Matching the Approximate Action Distribution
João A. Cândido Ramos, Lionel Blondé, Naoya Takeishi +1
In this paper, we introduce MAAD, a novel, sample-efficient on-policy algorithm for Imitation Learning from Observations. MAAD utilizes a surrogate reward signal, which can be deri…
Conditional Neural Relational Inference for Interacting Systems
Joao A. Candido Ramos, Lionel Blondé, Stéphane Armand +1
In this work, we want to learn to model the dynamics of similar yet distinct groups of interacting objects. These groups follow some common physical laws that exhibit specificities…
Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial Imitation Learning
Lionel Blondé, Pablo Strasser, Alexandros Kalousis
Despite the recent success of reinforcement learning in various domains, these approaches remain, for the most part, deterringly sensitive to hyper-parameters and are often riddled…
Relational Mimic for Visual Adversarial Imitation Learning
Lionel Blondé, Yichuan Charlie Tang, Jian Zhang +1
In this work, we introduce a new method for imitation learning from video demonstrations. Our method, Relational Mimic (RM), improves on previous visual imitation learning methods…
Sample-Efficient Imitation Learning via Generative Adversarial Nets
Lionel Blondé, Alexandros Kalousis
GAIL is a recent successful imitation learning architecture that exploits the adversarial training procedure introduced in GANs. Albeit successful at generating behaviours similar…